Presentation

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Line Segment
Experiment
Instructor: Professor Henderson, Thomas.
Student: Chun-Kai Wang
Outline

The line-segment program
– Prototype
– The architecture
– Meaning of each option

Examples
– How to read a pixel region picture in examples
– Examples of binary image
– Examples of gray-tone image

Issue of performance evaluate
The line-segment program
Prototype

function segments = lineSegs(img, mag_thres, zero_thres, len, varargin)
% input: img - The input image. It is a binary image or a gray-tone image. Here
we assume the foreground color is black and background color
is white.
mag_thres - The threshold value that determines the foregrounds
and the backgrounds.
zero_thres - The threshold value that determines how many variances
from the zero degree can be tolerated.
len - The len value for mark-seeds algorithm.
varargin - Options. Those are strings.
% output: segments - List of begin and end points of line segments.

Example call:
segs = lineSegs(im00, 0.49, 0.01, 9, ‘thin’, ‘sobel’);
The architecture
Meaning of each option (1)

Pre- edge detecting
– ‘thres’: Convert the input image to binary by Otsu’s method. This
option is automatically enable when the option ‘thin’ is enable.
The default value is disable.
– ‘thin’: Thinning the image with Matlab built-in thinning algorithm
(from “Thinning Methodologies-A Comprehensive Survey,” Louisa
Lam, Seong-Whan Lee, and Ching Y. Wuen, IEEE TrPAMI, vol. 14,
no. 9, pp. 869-885, 1992). This is design for the binary image
only. The default value is disable.
Meaning of each option (2)

Edge detecting
– ‘sobel’: Use Sobel edge detector. One and only one of options
‘sobel’ and ‘markseeds’ must be set enable. The default value is
enable.
– ‘sobelmerge’: Merge the two directions of edges that are
detected by Sobel edge detector into one. This option is
meaningful only when the option ‘sobel’ is enable. The default
value is disable.
– ‘markseeds’: Use Mark-Seeds edge detector. One and only one of
options ‘sobel’ and ‘markseeds’ must be set enable. The default
value is disable.
Examples
How to read a pixel region picture


A pixel region picture is a picture that shows values of each pixel in
some region of a image.
If a pixel region picture is for displaying line segments, each 1-pixel
wide horizontal line or vertical line is a line segment. For example,
there are eight line segments in the following pictures, each with a
unique color.
Examples of binary image (1)

The binary image and the region that we will use in the following
examples.
Examples of binary image (2)

Line segments with Sobel edge detector.
Examples of binary image (3)

Line segments with Sobel edge detector and edge merging.
Examples of binary image (4)

Line segments with thinning algorithm and Sobel edge detector.
Examples of binary image (5)

Line segments with thinning algorithm, Sobel edge detector, and
edge merging.
Examples of binary image (6)

Line segments with mark-seeds edge detector.
Examples of binary image (7)

Line segments with thinning algorithm and mark-seeds edge
detector.
Examples of gray-tone image (1)

The binary image and the region that we will use in the following
examples.
Examples of gray-tone image (2)

Line segments with Sobel edge detector.
Issue of performance evaluate

Original image MINUS Segments image.
– But not all of lines in the original image are one-pixel wide.


It is hard to find a automatic line segment program
performance evaluating tool because we need to know
line segments at the first hand to evaluate such a
program, but how can we find a perfect line segment
program at the first hand?
The dependable method that I can think of is to evaluate
the performance manually.
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