1044 IEEE TRANSACTIONS ON MAGNETICS, VOL. 43, NO. 3, MARCH 2007 Real-Time Orientation-Sensitive Magnetooptic Imager for Leakage Flux Inspection Shigeru Ando, Takaaki Nara, Nobutaka Ono, and Toru Kurihara The University of Tokyo, Tokyo 113-8656, Japan We propose a new system for magnetooptical imaging that can observe the distributions of the amplitude and phase of an ac leakage magnetic field on a steel sheet driven externally by a dipole or a quadrature (rotating dipole) magnet. The new system, which we call a three-phase correlation image sensor (3PCIS), can perform two-dimensional imaging and parallel lock-in detection of the intensity-modulated light generated by a magnetooptic film and polarimetric techniques. We apply the imaging system to the leakage flux inspection of surface or near-surface defects of steel sheets and to the grain observation of electromagnetic steels. The imaging system allows us to observe the amplitude and phase (polarity for dipole excitation and defect orientation for quadrature excitation) of vertical flux components. The imager is also applicable to nonlinearity visualization via the harmonic responses of driving frequency, and provides rich clues for the horizontal flux components through observation of fine movements of domain walls of the magnetooptic film. Index Terms—Correlation image sensor, Faraday effect, garnet, inspection, leakage flux, magnetooptic imaging. I. INTRODUCTION T HE magnetic flux leakage method [1], [2] is a technique for detecting flaws in steel sheets or pipes. An in-plane uniform magnetic field is excited in steel by external magnets. Then flaws generate a leakage magnetic field, which penetrates upward and downward the magnetic sensors attached to the surface of steel. One of the methods for sensing the leakage magnetic field is the use of a magnetooptic film (MOF) and polarimetric techniques [3]. When linearly polarized light is passed through the MOF, the field-induced Faraday rotation of polarization is converted into an intensity change by a fixed polarizer at the output. The magnetooptic imager (MOI) based on this principle is widely used for the nondestructive inspection of aging aircrafts [4]. It is followed by a charge-coupled device (CCD) and a processor for real-time image capture and enhancement [5]–[7]. The MOI is also used for detecting the flux associated with eddy currents around surface and subsurface structures [8], and for observing the interaction between a superconductor and a magnetic field [10]. Magnetooptic techniques provide also the unique possibility of observing dynamic processes with a high spatial resolution. The lock-in technique enables the detection of small leakages in a large stray magnetic field [3]. The vibrative motions of domain walls driven by an ac magnetic field can be synchronously detected [11], [12], although the realized systems are based on the off-line image sequence analysis [9], [13]–[15]. In this paper, we propose a novel MOI system using a new solid-state device, the three-phase correlation image sensor (3PCIS) [16]–[19]. The 3PCIS performs the synchronous detection and amplitude/phase demodulation of intensity-modulated light in real time on each pixel, and has a wide range of applications from a range finder to a real-time imaging ellipsometer [20]–[24]. The triadic symmetry of the three-phase (3P) architecture [19] enables a simple and symmetric pixel design and provides neccesary and sufficient degrees of freedom for determining three independent components, intensity, amplitude, and phase, of the modulated light. Another feature combined with the 3PCIS is the use of rotating magnetic excitation for visualizing the anisotropy and orientation of flaws. As compared with the former MOIs with a conventional CCD that accepts a time-averaged intensity within a frame interval, the proposed combination of 3PCIS and the an ac rotating magnetic field gives us several benefits: 1) real-time visualization; 2) availability of phase information (flux polarity for unidirectional excitation and defect orientation for rotational excitation) is available; 3) possible enhancement of sensitivity and resolution utilizing the skin depth of ferromagnetic materials; 4) imaging of nonlinear phenomena via the harmonic responses of driving frequency; and 5) reductions of disturbance and noise by lock-in detection. Also, the dense two-dimensional (2-D) data provide rich information for internal defects through an inversion process [25]–[27]. In Section II, we outline the principle and operation of the 3PCIS including the latest device we used, and then in Sections III and IV, we describe the details of the magnetooptic imager with several experiments to demonstrate the novel performances obtained by it. II. CORRELATION IMAGE SENSOR A. Correlation Detection and the electrical reference Let the local light input be . The correlation integral is then defined by signal be Digital Object Identifier 10.1109/TMAG.2006.888177 Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. 0018-9464/$25.00 © 2007 IEEE (1) ANDO et al.: MAGNETOOPTIC IMAGER FOR LEAKAGE FLUX INSPECTION 1045 TABLE I SPECIFICATION OF 3PCISS AND LOCK-IN CAMERAS USED IN EXPERIMENTS within the time interval , which provides an inner product between these functions to obtain the correlation coefficient (2) as an angle as in the vector space. When , it follows that is normalized (3) The roles of the correlation integral are therefore: 1) selecting signal components and removing noise components through a projection of a signal onto a subspace spanned by reference signals and 2) determining coordinate values of the signal components in the reference subspace. The device with similar roles is the lock-in CCD [28]–[30] that accepts only a binary reference signal. The 3PCIS accepts two arbitrary analog reference signals, and generates the correlations of light with them simultaneously; hence, we can use it for the demodulation of the amplitude and phase of a time-varying intensity field. 2 Fig. 1. The circuit and layout of the 64 64 pixel 3PCIS. V ; V , and V are the reference inputs and I is an input from the PD. The charges stored in the capacitors C are the sums of the mean intensity I and correlation I V between I and V . (a) Pixel circuit (3P multiplier/integrator). (b) Pixel layout. (c) Chip photograph. hi h i B. Pixel Structure and Operation As shown in Fig. 1(a), the 3PCIS consists of a photodiode PD, , and , capacitors of the same multiplier transistors , and . capacitance , and readout transistors The photogenerated current from the PD is split by , in proportion to their respective gate-source voltages and , and into the drain currents (4) ( : Boltzmann constant, : absolute temperature, : electron ), and charge, : gate coefficient, accumulated at three independent capacitors . By activating , and , charges are transferred to external capacitors and the capacitors are reset. The readout pulse is asynchronous to both the reference signal and the frame. Signal charges are converted to voltages by external charge amplifiers, hence the outputs are free from the imbalance of . No missing integration time occurs if the charges at adjacent frames are accumulated externally. The gate voltage can vary continuously over an integration interval. This enables the sensor to detect low-intensity, long-duration signals. The 64 64 pixel device was fabricated through the 1.2 m 2 poly-2 metal (2P2M) CMOS process provided by VLSI Design and Education Center (VDEC), University of Tokyo, and the 200 200 device was fabricated through the 0.35 m 2P3M CMOS imager process by SHARP Corp., Japan. Several parameters of these devices are summarized in Table I. The ratio between the cutoff frequency and the scan frequency means a figure of merit of the use of 3PCIS against the conventional camera. In the conventional camera, three or more frames are required for demodulation applications. This means the ratio is below 0.33. On the contrary, as shown in Table I, the ratio for the 3PCISs is 150 and 170. 1046 IEEE TRANSACTIONS ON MAGNETICS, VOL. 43, NO. 3, MARCH 2007 Fig. 2. Lock-in camera using 3PCIS. This enables parallel correlation detection with two arbitrary analog orthogonal reference signals supplied in the threephase form. The three correlation outputs are A/D-converted and transferred to a PC via the USB. Fig. 4. Vector diagrams for (a) three-line input and (b) two-line input of threephase reference-signal-conditioning circuit. plitude, and a correlation phase as follows. Let the time-varying be intensity on a pixel at the coordinates (5) where is the frequency of the modulated light, is the phase, is the amplitude, is the stationary background intensity, and denotes any time-varying light components except for the frequency and dc. As the reference signals of the 3PCIS, we input three sinusoidal waves whose frequency is and whose , and . Then, the 3PCIS generates initial phases are three outputs (6) Fig. 3. Reference voltage input circuit. The adequate input range for succeeding multipliers is about 0:5 V. The common mode voltage of g ; g ; and g is automatically removed. 6 where is the frame time. Hence, the intensity output is expressed as (7) C. Reference Signal Circuits The ac voltage range of reference signals is about mV at room temperature. For ease of use, the input circuit consists of differential amplifiers with a attenuation as shown in Fig. 3. For a triplet of 3P signals, the circuit produces another triplet of 3P signals [Fig. 4(a)]. When only two signals phase separation are input, it generates 3P referwith a ence signals [Fig. 4(b)]. In both cases, a common mode component, which affects the bias of multiplier and PD, is removed. For a single frequency application, the 3P reference signals are , where V. The correlation amplitude the least-squares criterion and phase are obtained based on (8) as (9) D. Amplitude/Phase Demodulation Three outputs from each pixel of the 3PCIS can be converted into a background (time-averaged) intensity, a correlation am- (10) ANDO et al.: MAGNETOOPTIC IMAGER FOR LEAKAGE FLUX INSPECTION 1047 TABLE II PARAMETERS OF MAGNETOOPTIC FILM FROM ITS TOP TO BOTTOM (FABRICATED BY SUMITOMO METAL MINING, LTD.) Fig. 5. Schematic diagram of imaging system with quadrature magnetic driver. The leakage flux distribution around defects is visualized using the Faraday rotation and magnetic domain movements in a magnetooptic film (MOF). The calculations are performed in real time by a PC from the A/D-converted outputs of the 3PCIS. III. MAGNETOOPTIC IMAGER A block diagram of the imager is illustrated in Fig. 5. This imager consists of a polarimetric optical system, exciting magnets and drivers, an oscillator for driving and reference signals, a 3PCIS and a PC for intensity/amplitude/phase imaging and display. A. Optical System As shown in Fig. 5, the system is built on a polarizing microscope (Nikon ME600, bright-field observation). The light from an incandescent lamp (100 W) passes through a polarizer and an MOF attached to the steel sheet. Then the light is reflected by the aluminum-coated back of the MOF, passes again through the MOF and analyzer, and is detected by the 3PCIS. The time-varying intensity distribution obtained using the Faraday rotation of a polarizing angle is demodulated by the 3PCIS into its distributions of amplitude and phase. The magnitude is selected from 5, 10, and 20, according to the observation schemes described in the following sections. The target is a steel sheet or plate attached to dipole or quadrature magnets driven by ac currents. The sinusoids in 0, 120, and 240 degrees of phase are supplied to the 3PCIS as reference signals for lock-in detection. B. Excitation Magnets The dipole excitation magnet consists of a cut core with a 120-turn coil and is fixed below the microscope stage. The quadrature excitation magnets consist of four ferrite bar cores connected by a horizontal toroidal one of the same type (TDK PC40). Two 200-turn coils on the opposite sides of the quadrature magnet are connected reversely, and the resultant two pairs of coils are driven by in-phase and quadrature phase sinusoidal currents. The driving current frequency range is from 100 Hz to 1 kHz. The current waveforms and reference signals of the 3PCIS are generated by the same synchronous multichannel D/A. The excitation magnets from the back of the specimen generate a nearly saturated in-plane magnetization in the steel sheet. This produces strong flux leakages around the flaws, cracks, and grain boundaries of the steel sheet. In addition, the ac rotational magnetic field excited by a quadrature magnet provides the homogeneous sensitivity to defects in any shapes and orientations. It also encodes the preferred orientation of the defects into the phase of time-varying vertical leakage flux. C. Magnetooptic Film (MOF) The parameters of the MOF we used are summarized in Table II. The MOF has an easy axis of anisotropy being normal to the surface. It also has a serpentine ( 17 m wide) domain structure with opposite magnetizations, which are expanding and shrinking in proportion to the vertical flux component. The average magnetization increases linearly with magnetic field and saturates when domains with an either polarity are exhausted. The domain structure changes slowly even in a stationary magnetic field and in a varying temperature. Hence, short-interval observations are only useful for the domain analysis of the MOF. The detailed domain structure can cause a nonlinear response depending on the diffraction orders involved [31], [32]. The linearity of the MOF was obtained in our system using a microscope optics with a large numerical aperture (NA). The gap between the film and the steel (liftoff) is the sum of the thicknesses of a mirror and a polyvinyl coating for protection ( 10 m). No magnetic-field bias is applied to the MOF as in the MOI using a conventional CCD [4]. The horizontal leakage flux component can cause a lateral domain motion. The movement direction of the boundary is parallel to the flux regardless of the signs of domain walls. The effect can be observed when the microscope magnitude is sufficiently large to capture the domain structure of the MOF. D. Resolution and Sensitivity The resolution can be divided into magnetic and optical ones. The optical resolution is simply the pixel size of the 3PCIS di- 1048 IEEE TRANSACTIONS ON MAGNETICS, VOL. 43, NO. 3, MARCH 2007 Fig. 6. Photographs of experimental setup with quadrature excitation magnet from back of specimen. (a) System overview. (b) Quadrature magnets. vided by the magnitude of the objective lens; hence, it is measured to be 20 m for 5 lens and 64 64 3PCIS, and 6 m for 5 lens and 200 200 3PCIS. The magnetic resolution and sensitivity are determined by the magnetic domain size of the film ( 17 m) and the liftoff. The domain size must be sufficiently smaller than the image resolution in order to remove noise due to domain structures and to exclude the effects of horizontal flux components [33]. Therefore, we introduce an appropriate defocus for the 200 200 3PCIS. The minimum resolvable distance beyond the domain size is nearly proportional to the liftoff [3], [10]. It is because the gradually smoothed flux distribution arises in proportion to the distance from the surface. For thick films, the distribution further reduces the sensible zone of garnet films for high-frequency components. IV. EXPERIMENTS 2 Fig. 7. Imaging of test grooves on steel plate with 200 200 pixel 3PCIS. In (a), (b), and (c), the left, middle, and right images, respectively, show the intensity, correlation amplitude, and correlation phase (see the chart in Fig. 8 for the color-angle correspondence). The image area size is 1.2 mm 1.2 mm. To compensate the deficient sensitivity, the driving current is much larger in (a) than (b) and (c). This causes a slight difference among the phase responses of (a), (b), and (c). (a) Image of groove 1 (W = 0:1 mm, D = 0:05 mm). 2 A. Imaging of Artificial Grooves For the imaging of vertical leakage flux components, the field of view of a pixel is adjusted to be sufficiently larger than the magnetic domains. The detailed structure of the magnetic domains is invisible. The modulated intensity with respect to the reference signal is in-phase where the flux is upward and counter-phase where it is downward. Fig. 7(a), (b), and (c) show images of known grooves depth length in mm are 0.1 0.05 1, whose width 0.1 0.1 1, and 0.2 0.2 1, respectively, on a 2 mm thick steel plate. A 150 Hz dipole excitation was induced in the direction perpendicular to the length. The phase histogram is shown in Fig. 8. Two peaks separated by about 180 degrees are for the upward and downward fluxes. The phase lag of about 30 degrees is caused by the inductance of the driving coil and the eddy current in the steel plate. After correcting the phase lag, the correlation responses across the grooves are plotted in Fig. 9(a)–(c). They are very similar to the results obtained by Numata et al. [3] using a photodetector and a lock-in amplifier. B. Imaging of Artificial Holes For the imaging of orientation dependence, the quadrature magnets are used. Fig. 10(a) and (b) shows images of the holes drilled in a conventional cold-rolled steel sheet and a grain-oriented (GO) electromagnetic steel sheet, respectively, under a 400 Hz ac rotational excitation. For the rolled steel sheet shown Fig. 8. Histogram of demodulated phase of leakage flux. The detected phase angles weighted by the correlation amplitudes are accumulated over 120 vertical lines near the center of Fig. 7(c). The upper chart shows the color-phase angle correspondence used in the phase images. in (a), homogeneous leakages around the hole can be observed in all directions. This shows that the internal magnetization is always parallel to the excitation direction, because the average permeability of the rolled steel is isotropic and uniform. Contrarily in the GO electromagnetic steel sheet shown in (b), the response shows only two phases, because the excited magnetization arises only in one direction that is equal to the easy axes of grains being oriented. ANDO et al.: MAGNETOOPTIC IMAGER FOR LEAKAGE FLUX INSPECTION 1049 Fig. 10. Imaging of drilled holes of conventional and grain-oriented (GO) electromagnetic steel sheet under rotational magnetic excitation. The left, middle, and right images show the intensity, correlation amplitude, and correlation phase, respectively. The image size is 1.2 mm 1.2 mm and the hole diameter is 0.6 mm. (a) Hole in conventional steel sheet. (b) Hole in grain-oriented (GO) electromagnetic steel sheet. 2 Fig. 9. Cross sections of in-phase correlation response across artificial grooves. Superpositions of 120 vertical cross sections near the center are displayed (200 200 3PCIS, 150 Hz dipole magnetic drives). The groove width W and depth D are indicated by a shaded rectangle in each graph. (a) Groove 1 (W = 0:1 mm, D = 0:05 mm). (b) Groove 2 (W = 0:1 mm, D = 0:1 mm). (c) Groove 3 (W = 0:2 mm, D = 0:2 mm). 2 C. Imaging of Grain Structures of Electromagnetic Steel Fig. 11(a) and (b), respectively, show images of strongly excited nonoriented (NO) and GO electromagnetic steels. A 400 Hz quadrature excitation was induced. In the GO electromagnetic steel, the leakage flux is usually very small in wide areas. A pattern similar to (b) that appears infrequently as a curvilinear segment will be due to grain boundaries or defects. Only two phases with a 180 degree difference are observed in the phase image of the GO steel. Each phase coincides with the easy axis direction of the GO electromagnetic steel. This shows that the excitation is effective only in the direction and the flux from the excited magnetization is going outside or returning to the steel at each segment. In contrast with the GO steel, the leakage flux from the NO electromagnetic steel shown in Fig. 11(a) is strong in wide areas and composed of tiny blobs with various phase angles. This shows that Fig. 11. Imaging of grain structures of nonoriented (NO) and grain-oriented (GO) electromagnetic steel sheets under 400 Hz rotational magnetic excitation using 200 200 pixel 3PCIS. (a) Nonoriented (NO) electromagnetic steel. (b) GO electromagnetic steel. 2 the excitation of the steel sheet in an average sense is uniform in all directions and that grains with an easy axis equal to the average magnetization angle produce the leakage flux. A planer leakage flux from each blob shows that the easy axis of the corresponding grain is not involved on the surface of the steel sheet. D. Obtaining Clues for Horizontal Flux Components In this case, the field of view of a pixel is adjusted to be sufficiently smaller so that thefine structure of the magnetic domains is visible. The change in intensity is caused by the movement of the magnetic domain walls. The domains are driven towards the flux direction when their walls are nearly perpendicular to the flux. Fig. 12(a) and (b) respectively show the defocused and focused observations of artificial flaws scraped in various directions under a 400 Hz quadrature excitation. The pixel size is 6 6 m, 1050 IEEE TRANSACTIONS ON MAGNETICS, VOL. 43, NO. 3, MARCH 2007 Fig. 12. Comparison of images under defocused and focused conditions. The object is artificial surface flaws scraped on a cold-rolled steel sheet (200 200 3PCIS, 400 Hz rotational excitation). (a) Defocused image. (b) Focused image. 2 whereas the domain size of the MOF is about 17 m. Hence, the detailed domain patterns are captured in the focused observation. In (b), the amplitude and phase images involve many striped or granular patterns whose period is nearly equal to the average domain width of the MOF. We observe in the phase image two types of repetition pattern in which the regions at opposite edges are in-phase or counter-phase. Comparing these regions in the defocused observation (a), we observe that the response vanishes in the counter-phase region, whereas it is preserved and smoothed in the in-phase region. This is caused by the different domain wall motions in these regions. The opposite walls are moving in the same direction in the former region and they are moving in the opposite directions in the latter region. In the former region, the domain is vibrating laterally while keeping its area. Contrarily in the latter region, the domain area is changing while keeping an average position of the domain. E. Imaging of Harmonic Responses We fix the driving frequency of the sinusoidal magnetic field and choose the reference frequency as an integer multiple of the driving frequency. The imager captures the amplitude and phase of the harmonic component of the resultant magnetic field. Fig. 13 shows the results. We consider two sources for the nonlinearity: a magnetic saturation of steel sheet and a binary change in magnetization in the MOF. However, in this experiment, the former is considered dominant. The flux leakage increases abruptly near the maxima of sinusoidal excitation, because the flux in the steel sheet saturates and goes out very easily. This causes the harmonic distortion of the leakage field. Since the leakage flux waveform is symmetric on time reversal, the responses are observed only for the odd-order harmonics [compare (a), (c), and (e) with (b) and (d)]. V. SUMMARY A new system for magnetooptical imaging was presented. The intensity modulated lights by an MOF in the flux and by polarimetric techniques were detected and demodulated in parallel by a 3PCIS. The imaging system was applied to the leakage flux Fig. 13. Imaging of harmonic components. The driving frequency is fixed at 150 Hz. The reference frequencies are varied as: (a) 150, (b) 300, (c) 450, (d) 600, and (e) 750 Hz. The 64 64 pixel 3PCIS, 20 object lens, and a dipole excitation magnet were used. (a) 150 Hz drive, 150 Hz reference. (b) 150 Hz drive, 300 Hz reference. (c) 150 Hz drive, 450 Hz reference. (d) 150 Hz drive, 600 Hz reference. (e) 150 Hz drive, 750 Hz reference. 2 2 inspection of surface and near-surface defects of steel sheets. Through several experiments, we showed that the system: 1) is capable of real-time visualizations of the magnitude and polarity of the leakage flux across defects with an ac dipole excitation, and the magnitude and orientation of anisotropic defects with an ac quadrature excitation; 2) can be used for the visualization of the magnetic nonlinearity of materials by harmonic leakage flux component imaging; and 3) provides rich clues for the horizontal flux components through observing fine movements of domain walls of the MOF. ANDO et al.: MAGNETOOPTIC IMAGER FOR LEAKAGE FLUX INSPECTION ACKNOWLEDGMENT The MOF and test steel sheets were provided by the Sumitomo Metal Industries, Ltd. and the Iron and Steel Institute of Japan, respectively. The authors are grateful to Prof. I. Sasada of Kyushu University and Prof. M. Hashimoto of The Polytechnic University for many helpful discussions. REFERENCES [1] R. Falk and M. Lambeck, “Optical detection of magnetic stray fields,” Opt. Commun., vol. 24, no. 1, pp. 129–132, 1978. [2] A. Hubert and R. Schafer, Magnetic Domains: The Analysis Of Magnetic Microstructures. New York: Springer, 1998. [3] T. Numata, T. Okatani, M. Ishihara, K. Onishi, S. Inokuchi, Y. Sakurai, and S. Matsushita, “Magneto-optical leakage flux testing of steel,” IEEE Trans. Magn., vol. 25, no. 5, pp. 4213–4215, Sep. 1989. [4] G. L. Fitzpatrick, D. K. Thome, R. L. Skaugset, E. Y. C. Shih, and W. C. L. Shih, “Novel eddy current field modulations of magneto-optic garnet films for real-time imaging of fatigue cracks and hidden corrosion,” Proc. SPIE, vol. 2001, pp. 210–222, 1993. [5] G. L. Fitzpatrick, D. K. Thome, R. L. Skaugset, and W. C. L. Shih, “Detection of cracks under cladding using magneto-optic imaging and rotating in-plane magnetization,” Proc. SPIE, vol. 2947, pp. 106–115, 1996. [6] Y. Deng, X. Liu, Y. Fan, A. Zeng, L. Udpa, and W. Shih, “Characterization of magneto-optic imaging data for aircraft inspection,” IEEE Trans. Magn., vol. 42, no. 10, pp. 3228–3230, Oct. 2006. [7] Z. Zeng, X. Liu, Y. Deng, L. Udpa, X. Xuan, W. C. L. Shih, and G. L. Fitzpatrick, “A parametric study of magneto-optic imaging using finite-element analysis applied to aircraft rivet site inspection,” IEEE Trans. Magn., vol. 42, no. 11, pp. 3237–3244, Nov. 2006. [8] S. Simms, “MOI: Magneto-optic/eddy current imaging,” Mater. Eval., vol. 51, no. 5, pp. 529–553, 1993. [9] A. Honda and K. Shirae, “Domain pattern measurements using CCD,” IEEE Trans. Magn., vol. MAG-17, no. 6, pp. 3096–3098, Nov. 1981. [10] M. R. Koblischka and R. J. Wijngaarden, “Magneto-optical investigation of superconductors,” Supercond. Sci. Tech., vol. 8, pp. 199–213, 1995. [11] V. S. Gornakov, V. I. Nikitenko, and V. T. Synogach, “Two-dimensional magnons and domain wall dynamics in yttrium iron garnet,” IEEE Trans. Magn., vol. 29, no. 6, pp. 2073–2076, Nov. 1993. [12] A. J. Moses, P. I. Williams, and O. A. Hoshtanar, “Novel instrument for real-time dynamic domain observation in bulk and micromagnetic materials,” IEEE Trans. Magn., vol. 41, no. 10, pp. 3736–3738, Oct. 2005. [13] B. E. Argyle, B. Petek, and D. A. Herman, “Optical imaging of magnetic domains in motion,” J. Appl. Phys., vol. 61, pp. 4303–4306, 1987. [14] H. Endo, S. Hayano, Y. Saito, M. Fujikura, and C. Kaido, “Magnetization curve plotting from the magnetic domain images,” IEEE Trans. Magn., vol. 37, no. 4, pp. 2727–2730, Jul. 2001. [15] U. Park, L. Udpa, and G. C. Stockman, “Motion-based filtering of magneto-optic imagers,” Image Vis. Comput., vol. 22, no. 3, pp. 243–249, 2004. [16] S. Ando, K. Nakamura, and T. Sakaguchi, “Ultrafast correlation image sensor,” in Proc. IEEE Workshop on CCD and AIS, Bruges, Belgium, 1997. [17] S. Ando and A. Kimachi, “Time-domain correlation image sensor: First CMOS realization of demodulator pixels array,” in Proc. IEEE Workshop on CCD and AIS, Karuizawa, 1999, pp. 33–36. [18] A. Kimachi and S. Ando, “Time-domain correlation image sensor: CMOS design and integration of demodulator pixels,” Proc. SPIE, vol. 3950, pp. 220–227, 2000. [19] S. Ando and A. Kimachi, “Correlation image sensor: Two-dimensional matched detection of amplitude modulated light,” IEEE Trans. Electron Devices, vol. 50, no. 10, pp. 2059–2066, Oct. 2003. [20] A. Kimachi, T. Kurihara, M. Takamoto, and S. Ando, “A novel range finding system using correlation image sensor,” Trans. Inst. Elect. Eng. Jpn., vol. 121-E, no. 7, pp. 367–375, 2001. [21] A. Kimachi, T. Imaizumi, A. Kato, and S. Ando, “Spectral matching imager using correlation image sensor,” Trans. Inst. Elect. Eng. Jpn., vol. 122-E, no. 4, pp. 200–206, 2002. [22] T. Kurihara, N. Ono, and S. Ando, “Surface orientation imager using three-phase amplitude-modulated illumination and correlation image sensor,” Proc. SPIE, vol. 5013, pp. 95–102, 2003. [23] T. Kurihara and S. Ando, “Real-time 2-D phase-sensitive vibrometer using heterodyne moire and correlation image sensor,” in Proc. 2004 ICO Int. Conf. (ICO’04), 2004, pp. 617–618. 1051 [24] T. Shimizu, T. Kurihara, N. Ono, and S. Ando, “Real-time imaging ellipsometer using rotating polarizer/analyzer and correlation image sensor,” in Proc. 2004 ICO Int. Conf. (ICO’04), 2004, pp. 423–424. [25] J. Haueisen, R. Unger, T. Beuker, and N. E. Bellemann, “Evaluation of inverse algorithms in the analysis of magnetic flux leakage data,” IEEE Trans. Magn., vol. 38, no. 3, pp. 1481–1488, May 2002. [26] T. Nara, S. Hayashi, and S. Ando, “Magnetic dipole estimation from the measurement of complex gradients,” in Proc. SICE Annual Conf., Sapporo, Japan, 2004, pp. 875–878. [27] T. Nara and S. Ando, “Projective method for the inverse source problem of the poisson equation,” Inverse Problems, vol. 19, no. 2, pp. 355–370, 2003. [28] J. O. Stenflo and H. Povel, “Astronomical polarimeter with 2-D detector arrays,” Appl. Opt., vol. 24, no. 22, pp. 3893–3898, 1985. [29] H. P. Povel, C. U. Keller, and I.-A. Yadigaroglu, “Two-dimensional polarimeter with a charge-coupled-device image sensor and a piezoelastic modulator,” Appl. Opt., vol. 33, no. 19, pp. 4254–4260, 1994. [30] T. Spirig, P. Seitz, O. Vietze, and F. Heitger, “The lock-in CCD—Twodimensional synchronous detection of light,” IEEE J. Quantum Electron., vol. 31, no. 9, pp. 1705–1708, Sep. 1995. [31] N. Itoh, H. Minemoto, D. Ishiko, and S. Ishizuka, “Optical magnetic field sensors with high linearity using bi-substituted rare-earth iron garnets,” IEEE Trans. Magn., vol. 31, no. 6, pp. 3191–3193, Nov. 1995. [32] L. Wenzel and A. Hubert, “Simulating magneto-optic imaging with the tools of Fourier optics,” IEEE Trans. Magn., vol. 32, no. 5, pp. 4084–4086, Sep. 1996. [33] I. Nistor, C. Holthaus, I. D. Mayergoyz, and C. Krafft, “Nonscanning imaging of two-dimensional magnetic patterns with submicron resolution using thin garnet films,” IEEE Trans. Magn., vol. 42, no. 10, pp. 3255–3257, Oct. 2006. Manuscript received July 22, 2005; revised November 11, 2006. Corresponding author: S. Ando (e-mail: ando@alab.t.u-tokyo.ac.jp). Shigeru Ando (M’80) received the B.E., M.E., and Dr. Engr. degrees in mathematical engineering and information physics from the University of Tokyo, Tokyo, Japan, in 1974, 1976, and 1979, respectively. He joined the Faculty of Engineering of the University of Tokyo in 1979, served as Associate Professor starting in 1987, and is currently Professor in the Department of Mathematical Engineering and Information Physics, Graduate School of Engineering of the University of Tokyo. He works on research and education on sensors, image processing, signal processing, optical and acoustic sensing, measurement, and electric circuits. Prof. Ando is a member of the Optical Society of America, the Acoustical Society of America, the Institute of Electrical Engineers of Japan (IEEJ), the Acoustical Society of Japan, the Optical Society of Japan, and the Society of Instrument and Control Engineers (SICE). Takaaki Nara (M’98) was born in Tokyo, Japan, on March 20, 1973. He received the B. Engr. and M. Engr. degrees in mathematical engineering and information physics, and the Dr. Engr. degree in advanced interdisciplinary studies from the University of Tokyo, Tokyo, Japan, in 1995, 1997, and 2000, respectively. He is currently a Lecturer in the Graduate School of Information Science and Technology, the University of Tokyo. His areas of interest include analyses and measurements in inverse problems. Nobutaka Ono received the B.E., M.S., and Ph.D. degrees from the University of Tokyo, Tokyo, Japan, in 1996, 1998, 2001, respectively. He joined the Graduate School of Information Science and Technology, University of Tokyo, in 2001 as a Research Associate, and became a Lecturer in 2005. His research interests include acoustic signal processing, speech processing, music processing, sensing and measurement, and auditory modeling. He has been a secretary of the technical committee of psychological and physiological acoustics in Japan since 2005. Toru Kurihara was born on January 18, 1978, in Japan. He received the B. Engr., M. Engr., and Ph.D. degrees from the University of Tokyo, Tokyo, Japan, in 2000, 2002, and 2005, respectively.