Han et al.: Automatic Volume Control System for Compensation of Volume Difference Between TV Channels
1197
AUTOMATIC VOLUME CONTROL SYSTEM FOR COMPENSATION
OF VOLUME DIFFERENCE BETWEEN TV CHANNELS
Kyu-Phil Han,’ Kun-Woen Song,’ Zoong-Hee Kim,‘
Gwang-Choon Lee,* and Yeong-Ho Ha’
’School of Electronic & Electrical Eng., Kyungpook Nat’l Univ.
Taegu 702-701, Korea
‘Display Product Research Lab. of LG Electronics Inc.
Kumi 730-360, Korea
Abstract - The sound levels of TV channels vary
greatly according to modulation and demodulation
rates. When the television channel or input mode is
changed, users have to adjust the volume in order
to obtain a proper level of sound.
In this paper, an automatic volume control
system is proposed to compensate for the volume
difference which occurs with channel changing. A
simple power estimation based on the symmetry
property of sound and a selective volume control
algorithm using a 3-step compensation are
presented. The proposed system is designed using
consumer ICs for easy implementation to current
audio media. In addition, a filter is used to revise
the system function in order to model the
frequency response of the designed system upon
that of human at a normal hearing level.
As the experimental results in TV set, it is
shown that the volume fluctuation is considerably
reduced.
I . Introduction
“loudness curve” is taken into consideration in the
system design.
II. Specific
characteristics of sound
The human ear is responsive to frequencies
from about 20 to 20,000Hz covering a range of
10 octaves. In the voice signal, the major part of
the energy is distributed around 1,00OHz, because
the first formant of the: vocal tract is at this
frequency[4,5]. In general, if lower frequencies of
speech are removed, the articulation index does
not change markedly until frequencies above
S00Hz are removed. If low frequencies between
500 and 2,500Hz are removed, the articulation
index drops sharply. On the other hand, if high
frequencies beyond 2,500Hz are removed, 80%
articulation remains, lbut the removal
of
frequencies above 1,000Hz leads to impractical
communication systems since only 40% o f the
words spoken are correctly identified[2]. Roughly
speaking, 90% of the total power lies between
S O 0 3,SOOHz.
However, the human ear is most sensitive to
frequencies from about 2 to SkHz and least
sensitive to sounds at the extreme frequencies of
the audible range[3]. The most sensitive band of
sound is slightly diffxent from the energy
concentrated band. Therefore, in order to
compensate the volume according to the
sensitivity of humans, the power of sound which
is mixed by voice, music, and so on has to be
calculated in accordance with the frequency
response of humans. As shown in Fig. 1, the
contour line shows an equivalent loudness which
is judged by the listener to be of the same power
level, so called “loudness curve”, and it is a real
-
The reproduced sound levels in TVs are
different between channels due to different
modulation factors. A constant sound level
without abrupt changes due to channel switches
would be more convenient for the TV viewer.
In order to compensate for the volume difference,
without requiring user, the power of the input
signal has to be automatically calculated and
adjusted.
In this paper, a system with power estimation,
selective volume compensation of 3-step7 and a
simple hardware structure is presented. Since
human response is different according to frequency
[1,2], the hearing sensitivity[3] which is called the
Contributed Paper
Manuscript received August 14, 1997
0098 3063/97 $10.00 1997 IEEE
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
IEEE Transactions on Consumer Electronics, Vol. 43, No. 4, NOVEMBER 1997
1198
response curve established through experimentation.
The phon is a unit of the level of loudness. The
level of a sound, in phons, is numerically equal
to the intensity level(in decibels) of a pure lkHz
tone.
Another feature of sound is unbiased property
that the signal is symmetric to zero level[4]. This
is a popular assumption for speech processing
[6,7]. It means that the moving average during
several ten milliseconds is always zero. Also, it
shows that the power can be estimated with the
half of the signal. Examples of symmetry are
shown in Fig. 2.
130
120
110
100
90
g
80
-E
70
2
60
E
40
50
while processing other jobs, the power estimation
is a trivial task. However, it is impossiblc to
calculate the power with the current capability of
processors. In order to implement the volume
system in TVs, a simple algorithm for the
estimation is needed.
It is assumed that the total power of sound
may be calculated by the upper or lower side of
the signal because of the symmetric property as
mentioned above. A power estimation method
using the width of the signal as being greater
than a threshold is proposed The threshold value,
classifying a frame into a sound or a silence
interval, is set by several experiments. From the
experiments, 10% of the maximum value is
suitable as the threshold. An example of this
division is shown in Fig. 3. It shows only a
threshold selection. An example of thresholding is
represented in Fig. 4 and the power is estimated
using only the upper half of the signal as shown
in Fig. 4(b).
30
20
10
0
-10
20
50
100
200
500
1,000 2000
5.000 10,00020,0000
Frequency in Hz
Fig. 1. The loudness curve.
Sample no
Sample na
(a)
(b)
Fig. 2. Examples of symmetry. These signals were
digitized by 20kHz rate and 16-bit quantization.
In the case of the articulation (a)“one” and @)
“two” in Korean.
(b)
Fig. 3. An example of division. The threshold is
10% of the maximum value. (a) Speech signal
with 25,000 samples, 22.05kHz sampling rate, and
16-bit quantization. (b) Sound and silence intervals
which have the value “1” and “0”, respectively.
III. The proposed power
estimation algorithm
3.1 Principle of the proposed algorithm
If the microprocessor of current audio media
in TVs can sample the signal with a 40kHz rate
It is known that the power of sound is
proportional to the root-mean-square value, but
this is not true for humans because of frequency
response. Therefore, the transfer function of the
designed system should needs to be revised to
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
Han et al.:
Automatic Volume Control System for Compensation of Volume Difference Between TV Channels
take account of human response. The detailed
system function will be mentioned in section 4.3
after the system design.
1199
directly proportional to the accumulation time
which is the sum of the widths in several frames.
Thus, the estimation value, V m , can be defined
by
V,,
‘+““TTTT i
Sample no
‘tax-
=
mt,
+
c
( 31
where t, , m , and c are the mean accumulation
time within several frames, the slope, and the
bias value of the estimation function, respectively.
w
68
1
I B
2
8
,
Sampleno
(a)
(b)
Fig. 4. An example of thresholding. (a) The input
signal, (b) the clipped signal.
framee(50ms)
I
To treat the frequency response for human, the
perceived power, P,, , is defined as follows.
thresholding
ti
where a ( n ) , v ( n ) , and N, are weighting
functions depending on a perception ratio, a
sampled signal at the nth point, and the number
of the samples, respectively. We can say that Eq.
(1) consists of a constant a ( n ) which is related
to frequency and the rms value. Let s ( n ) be an
actual transfer function of the designed system
and f ( n ) be a filter which makes a ( n ) the
inverse of loudness. The a ( n ) can be written as
>
fsnd
*
frame count= I O ?
calculate fa
~k----j--z
estima e rms
and its Fourier transform
where A ( f ) , S ( f ) , and F ( f ) denote the
Fourier transformed functions. Because desired
A ( f ) and designed S ( f ) are known, the
F ( f ) can be simply determined. From now an,
we refer to the A (f) as the total transfer
function of the system.
To complete the power estimation procedure,
the VrmSvalue of the second term in Eq. 11) has
to be calculated. The width of the signal shown
in Fig. 4(b) is used for the estimation. Then, it is
shown from Fig. 6 that the rms value of sound is
L
Fig. 5 . Flow chart of the simulation.
3.2 V,,
estimation
The simulation procedure is shown in Fig. 5.
After the sampled signal is classified into a sound
or a silence frame by a threshold value, the
maintenance time
over the
threshold
is
accumulated in the sound frame. A frame set
consists of ten frames and t, is the mean
accumulation time of the frame set. tl and tsnd
denote the accumulation time of one frame and
the minimum time of a sound frame, respectively.
Finally, we check that the m
s value can be
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
IEEE Transactions on Consumer Electronics,Vol. 43, No. 4, NOVEMBER 1997
1200
approximated by Eq. (3). Table I shows the
case of a voice signal and Table 11 shows that
of music. From this data, m and c were
calculated to 1.4 and 5, respectively. Since the
dimensions of t, (millisecond) and rms value
(volts) are different, the question arises how to
connect the differences of the units. However, it
is more important that tu is proportional to the
rms value, so that the difference in unit is
beyond the concern.
The result of 7,200 frame sets is shown in
Fig. 6. From these results, we can conclude that
V,, is proportional to and estimated by t,.
P
38 003
ic 00
i
j
Frame length 50ms
Data classic jazz pop and speech
Root mean square value / la
=
-1 02
>
1
2I5M
-
~~~~~
Table I . The comparison of V,, and tu for a
8-bit quantized voice signal(Max. value: 100,
threshold:10. 1 frame length:50ms, and tsnd:O.lms).
__
-
Framc
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
tl
-
00
4.8
18.0
13.4
18.7
18.8
18.4
10.2
3.4
8.1
__
1.7
13.0
0.6
0.0
00
4.9
9.4
8.9
0.0
0.0
0.0
0.0
4.8
9.6
19 3
18.2
21.3
19.4
9.3
7.5
2.1
__
~
mcan of V,,,
Vrms
2.37
11.43
29.16
20.25
23.11
23.34
24.78
13.60
7.26
15.14
5.06
18.38
3.56
2.26
2.62
10.29
16.17
14.46
2.37
2 44
2.35
2.51
9.69
14.83
25.96
22.81
26.58
25.37
14.96
13.27
5.12
17.04
3.85
7.76
10.14
14.88
5"k_..
aoo
002
Accumulation time (ms)
Fig. 6. The relation between mean of V,,
t, (Total 7,200 frames are used).
IV. System
and
Implementation
The proposed algorithm
current TV sets as follows.
is
implemented in
4.1 The audio system in a TV
A signal received from an antenna, which has
passed through tuning and a demodulation block,
enters the AlV(audio and video) switch as shown
in Fig. 7 . Air or line input and video or audio
signals are selected by the switch. In an audio
control unit, the volume, bass, tone, surround, and
balance, etc. are adjusted and the selected and
adjusted signal is then transferred to the speaker.
Table 11. The comparison of VmT and tu for a
8-bit quantized music signal(Max. value:100,
threshold:lO, 1 frame length:50ms, and tsnd:O. lms).
~
Frame
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
tl
__
14.8
14.6
12.9
13.8
14.1
13.7
13.8
15.0
13.5
15.3
___
13.7
11.7
13.6
14.1
12.4
11.8
14.0
14.1
13.8
13.2
12.9
__
15.0
12.5
12.9
24
25
26
27
28
29
30
12.3
12.0
15.8
11.2
~
11.5
119
10.3
V"
18.24
22.59
16.91
17.90
20.32
18.14
19.43
19.87
18.86
21.33
18.82
14.15
16.87
17.83
15.15
16.38
17.66
18.15
17.90
18.79
15.28
19.32
16.48
mean of VI,,
19.36
13.21
16.99
12.54
17.02
18.35
17.93
16.99
19.89
15.72
16.40
16.17
12.98
Fig. 7. Block diagram of the audio system in a TV.
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
Han et al.: Automatic Volume Control System for Compensation of Volume Difference Between TV Channels
4.2 The proposed automatic volume
control unit
Since only one volume control unit is used in
a TV, as shown in Fig. 7, the level which is set
by the user can be changed at every alteration.
Therefore, another volume control chip has to be
inserted in front of the existing audio control unit
to preserve the absolute level set by user.
The total and the detailed block diagram of
the proposed system are presented in Figs. 8 and
9, respectively. The proposed automatic volume
control system consists of three main stages
which are the low pass filter(LPF) and amplifier,
the trigger and counter, and the signal analysis
and control parts.
Y
1201
In order to operate the trigger circuit, the voltage
gain of the amplifier should be 20 times, or
26dB. The reason why thle gain must be 20 is
because the trigger circuit was designed with a
BJT(bipo1ar junction transistor) and the turn-on
voItage(VBE) of the trarisistor must be over
0.7volts. When signals which are higher than the
noise level are inputted, the trigger circuit is
activated.
The filter is classified into the second-order
multiple feedback type, because R3 and CZ are
connected between the input and output nodes.
The advantage of the filter is that it is more
stable than the Butterworth or Chebyshev group
because of multiple feedback. Another merit is
that the gain is easily controlled by the ratio of
RI and R3. The cut-off frequency of the filter is
calculated by
r+
s'gna'
Fig. 8. Block diagram of the audio system with an
automatic volume control unit.
LPF and
+
amplifier
-
Trigger
circuit
-
~ous;;;;;AS~;
+
DIA
convelter
Fig. 10. Multiple feedback LPF and amplifier.
I
Microprocessor
(signal analysis
and control)
Signal input
Volume control
chip
4.2.2 The second stage
Signal output
b
Fig. 9. Block diagram of the automatic volume
control unit.
4.2.1 The first stage
At first, the sound is amplified by a LPF and
an amplifier circuit as depicted in Fig. 10.
Generally, in a TV signal, the magnitude of sound
is 0.8Vp-p and the noise level is about 0.035volts.
The amplified signal is entered into the trigger
circuit. The input of the AND gate is the
transistor output and the clock pulse. And the
output of the AND gate is inserted into the next
stage counter as shown in Fig. 11. Then, the rms
value of the sound is converted into binary code.
A timer and an AND gate are used for the
clock generator and multiplier, respectively.
Because of t- 1 gating error in the multiplication,
a high frequency clock of above 20kHz has to be
used to reduce the error. However, the higher
clock is used, the more bits of the counter are
needed. According to some experiments, a 1OOkHz
clock is sufficient. For example, if a lkHz signal
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
IEEE Transactions on Consumer Electronics, Vol. 43, No. 4, NOVEMBER 1997
1202
is inputted to the second stage, the output is
equal to those of Fig. 12. The black sections of
Fig. 12(c) represent a 1OOkHz clock.
+r
C3202
5 1K
To sum up the total flow of the designed
system, the input signal is selectively amplified by
the LPF which then activates the trigger circuit.
The triggered pulse intermits the clock. Then the
output clock which has been gated by the input
signal is inserted into the counter. Finally, the
signal analysis part reads the count periodically
and estimates the rms value of the signal. The
volume is finally adjusted by the value.
+5v
+5v
-5v
b
Ro
15P
15K
8
13
4
14 15
3
16
0
2
3
Fig. 11. Trigger, clock generator, and multiplier
circuit
LSB
La_
PR
PR
(c)
Fig. 12. An example of a 1kHz signal in the
second stage. (a), (b), and (c) represent the input
signal, the output of the trigger circuit, and the
multiplier output, respectively.
Q-*
J
counter
Input
In order to reduce the port waste, a DAC
(digital to analog converter) is used. If a parallel
port is available, the operational amplifier and
DAC are omitted from the circuit. As shown in
Fig. 13, the output is inserted into the signal
analysis and control unit in Fig. 9.
DAC
VOUt
c>CK
K
CLR
J
Q-B
-
<)CK
0
K
CLR
MSB
n
PR
PR
-8
. - ..
0
0-8
J
J
0
2 ,CK
.-C,CK
K
Q
CLR
K
Q
CLR
Fig. 13. Asynchronous counter and DAC.
4.2.3. The third stage
The signal analysisicontrol unit calculates the
current power, monitors the channel or mode
changes, and adjusts the volume. In order to
reduce the awkwardness for humans and decrease
the compensation error, the maximum level for a
volume change is limited and the three step
adjustment is used in this compensation.
The control flow is shown in Fig. 14. First,
the constants are initialized and the compensation
routine will start if a mode or channel change
occurs. The frame count, the silence count, and
the threshold are set at 30, 50, and 64 in
decimal, respectively. 15ms is set as the frame
length. And if 50 consecutive frames are all
silence frame, the volume is set by the default
value. The reason that it can not wait beyond this
time is because of awkwardness. Thus, the
minimum
time
for
one
compensation is
450ms(30frames X 15ms). Normally, since silence
and sound frames are usually mixed, the average
time for compensation is about 600ms. In current
television sets, a mute time of about 300ms is
inserted after every channel change. If the mute is
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
Han et al.: Automatic Volume Control System for Compensation of Volume Difference Between TV Charnels
continued until the end of the three step
compensation, i.e. for about 1.5 - 1.8s, users feel
uneasy. Then the mute is cleared after the first
adjustment. Since the fluctuation of sound is
severe, the three step compensation and the
limitation of the maximum volume change are
more effective.
Through the experiments, the volume step
according to a power difference is determined and
the mean(defau1t) level of the volume is set to
the center of the most linear scale on the volume
curve. When the total volume has 128 scales, it
is appropriate that the default level is set to a
64th scale and the maximum change is 6 steps.
-
-ss
initialize constants
read the count
no
sound loop: yes
silence loop:
1203
4.3 Analysis and revision of the proposed
system
As explained in seclion 2, the frequency
response of the LPF is an important factor to
consider human cognition. Unlike humans, the
response of the system has to be constant for a
frequency. Actually, the response of the system
without the filter(LPF) is not constant. The trigger
and the multiplier are more sensitive to high
frequencies. It means that the estimation power is
higher than the actual power in the frequencies. It
is expected that the accumulation of the +- 1
gating error acts as a dominant term in the
multiplier. The error can be reduced by using a
high frequency clock. However, this is not
suitable for implementation in current audio
systems. Even if the response of the system is
either constant or not, a filter must be used to
correct the system function. For example, when a
correction filter is not used and a high frequency
is inputted, humans feel a low power but the
system is actually not.
The system was tested without a filter. It was
shown that the sensitivity of a 20kHz sine wave
is 1.7 times higher than that of a 20Hz. That is
to say, the elapsed time of 20Hz from 00 to FF
in hexadecimal is about 25ms, and the time of
2OkHz is 15ms. Also the slope of the response is
like an exponential curve. Therefore, the response
function, F,,, (f), of the second stage can be
approximated as
e,
set default volume level
1 compare the previous level 1
7
I
adjust volume
&
step three?
Fig. 14. Flow chart of the volume control routine.
where a is a constant. Substituting f = 20k and
Fra0(f) = 1.7 into Eq. (5), a is calculated by
a =
~
lnlS7
20000
=
0.000027
The response function, t'xp(O.O00027J, is shown
in Fig. 15. In order to consider the inverse of
loudness, the cut-off frequency of the filter has to
be about lOkHz, then the elements of Eq. (4) are
set by
1
f"
= -300~
= 10.402kHz
*
300~
(7)
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
E E E Transactions on Consumer Electronics, Vol. 43, No. 4, NOVEMBER 1997
1204
According to Eq. (2-2), the system function,
S ( f ) , is equal to F,,, (f).Therefore, the total
transfer function can be obtained by Eq. (2-2).
Fig. 17 shows the A (f).
Generally, normal hearing level corresponds to
the fourth or fifth curve from the bottom in Fig.
1[3]. When compared with the curves, the transfer
function of the total system is an inverse form of
the “loudness curve” and more sensitive from 2k
to 5kHz. Therefore, we can say that the system
takes the human response into consideration.
o+ .......r...............,........,
IOOHz
1OHz
exp(0.000027*
1 .OKWZ
IOKHz
IOOKHz
Frequency)
Frequency
Fig. 15. The response curve of the second stage
which contains the counter and the multiplier.
The response of the filter shown in Fig. 10 is
depicted in Fig. 16.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
I
V . Experimental results
For the evaluation of the proposed system, the
root-mean-square values of the input and the
compensated signal are numerically compared as
shown in Table III. Subjective hearing tests were
undertaken by twenty people. In the subjective
tests, it is shown that the proposed system acts
properly.
Table D. The comparison of the two rms values
[unit:volt].
air
@.a”+ ..............l.
1OHz
0
.
r
,
.
IOOHZ
1. UKHz
IOKHz
IOOKHr
lCHl I
CH2 I
CH31
TA1 1
0.301
0.333
0.380
0.368
0.452
0.423
0.437
0.438
0.292
0.617
0.791
0.524
0.025
0.408
0.483
0.5 14
0.446
0.001
u(u2:+)
Frequency
Fig. 16. The transfer function of the filter shown
in Fig. 10. The curve is plotted by PSPICE.
.........................................................
I
(tape) . TA3
midin CD1
CD2
(‘Dl ICD3
variance
I--.-
VI. Conclusion
D.7“+ .............................................................
1OH2
IOOHz
1. OKHz
IOKHz
IOOKHZ
o
U(U2:+)*exp(Ci.O00027*
Frequency)
Frequency
Fig. 17. The total response curve of the designed
system.
The volume fluctuations in TVs caused by the
modulation and demodulation ratio of the air
signal, the playing and recording power of a
stored signal, etc. are considerably reduced by the
proposed system. Since the system is designed
using consumer ICs such as an operational
amplifier, a timer, a JK FIF, it can be easily
applied to current products with a low cost. In
addition, to model the frequency response of the
designed system on that of a human at a normal
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.
Han et al.: Automatic Volume Control System for Compensation of Volume Difference Between TV Channels
hearing level, a 2nd-order multiple feedback LPF
is used. Thus, the proposed system can hold a
constant volume at normal hearing level.
Although the human response to frequencies is
considered,
the
linear
compensation
was
accomplished at the most linear scale of the
volume. Therefore, a logarithmic volume scale can
be used for the compensation.
References
1205
Kun-Woen Song received the B.
S. and M. S. in Electronic
from
Kyungpook
Engineering
National University, Taegu, Korea,
in 1993 and 1995, respectively,
and is currently a Ph. D. student
in the Department of Electronic
Engineering, Kyungpook National
University. His main interests are
in digital signal processing,
non-linear
image
processing,
image coding, and computer
vision.
[I] Corsi, J. F., Experimental Psychology of
Sensory Behaviour, Holt, New York, 1967.
[2] Breger, L., Clinical Cognitive Psychology,
Prentice-Hall, Englewood Cliffs, N.J., 1969,
[3] Donald G. Fink and Donald Christiansen,
Electronics Engineers’ Handbook, 3rd ed.,
McGraw-Hill, New York, 1989.
141 L. Rabiner and B. H. Juang, Fundamentals of
Speech Recognition, Prentice-Hall Englewood
Cliffs, N.J., 1993
[5] Christopher Schmandt, Voice Communicaion
with Computers, MIT lab. 1993.
[6] S. B. Davis and P. Mermelstein, ‘Comparison
of parmetric representations of monosyllabic
word recognition in continuously spoken
sentences,” IEEE Trans. Acoust., Speeh, and
Signal Processing, vol. ASSP-28, no. 4, pp.
357-366, Aug. 1980.
[7] V. Zue, J. Glass, M. Phillips, and S. Seneff,
“Acoustic
segmentation
and
phonetic
classification in the SUMMIT system,” in
Proc. IEEE Int. Con$ on Acoust., Speech,
and Signal processing, pp. 389-392, May
1989.
Biography
Kyu-Phil Han received the B. S.
and
M.
S. in Electronic
Engineering from
Kyungpook
National University, Taegu, Korea,
in 1993 and 1995, respectively,
and is currently a Ph. D. student
in the Department of Electronic
Engineering, Kyungpook National
University. His main interests are
in digital signal processing, image
processing, and computer vision.
Zoong-Hee Kim received the B. S. and M. S. in
Electronic Engineering from
Kyungpook National
University, Taegu, Korea, in 1970 and 1997, respectively,
and is working as a manager in Display Product Research
Lab. of LG Electronics Inc. Korea. His main research
interests are in digital signal processing, circuit design,
and TV signal processing.
Gwang-Choon Lee received the B. S. and M. S. in
Electronic Engineering from Irha University, Inchon, and
Kyungpook National University, Taegu, Korea, in 1970
and 1995, respectively, and is working as a director in
Display Product Research Lab. of LG Electronics Inc.
Korea. His main research intixests are in digital signal
processing and TV signal proce:ssing.
Yeong-Ho Ha received the B. S.
and hI. S. degrees in Electronic
Engineering
from
Kyungpook
National University, Taegu, Korea,
in 1976 and 1978, respectively,
and P’h. D. degree in Electrical
and Computer Engineering from
the University of Texas at Austin,
Texas, 1985. In March 1986, he
joined
the
Department
of
Electronic
Engineering
of
Kyungpook National University,
as an Assistant Professor, and is currently a Professor. His
main research interests are in image processing, computer
vision, TV signal processing, and digital signal processing.
He served as TPC co-chair of 1994 IEEE Intemational
Conference on Intelligent Signal Processing and
Communication Systems. He is, a member of IEEE, Pattem
Recognition Society, IS&T, K.orea Institute of Telematics
and Electronics, and Korean Institute of Communication
Sciences.
Authorized licensed use limited to: Minnesota State University-Mankato. Downloaded on January 29,2021 at 02:53:16 UTC from IEEE Xplore. Restrictions apply.