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109 changes: 109 additions & 0 deletions Readme.md
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ABOUT THIS PROJECT
The source files included in this repository (folder 'src') contain the source
code of ELSDc (Ellipse and Line Segment Detector, with Continuous validation),
described in 'Joint A Contrario Ellipse and Line Detection', by
V. Patraucean, P. Gurdjos, R. Grompone von Gioi; this is the enhanced version
of ELSD, published in
'A Parameterless Line Segment and Elliptical Arc Detector with Enhanced
Ellipse Fitting', V. Patraucean, P. Gurdjos, R. Grompone von Gioi, ECCV2012.

Corresponding author: viorica patraucean vpatrauc@gmail.com

Test online the detector by uploading your own images at
http://dev.ipol.im/~jirafa/ipol_demo/elsdc/ (user: demo, pass:demo).

This program is free software: you can redistribute it and/or modify it under
the terms of the GNU Affero General Public License as published by the Free
Software Foundation, either version 3 of the License, or (at your option) any
later version.

REQUIREMENTS
ELSDc requires CLAPACK/CBLAS library for some linear algebra computations.
Version 3.2.1 was used.


SOURCE CODE FILES (folder 'src')
'main.c' contains the main() function; entry point into the application,
calls IO functions and the detection function.
'curve_grow.c' contains functions for region grow (gather neighbour pixels
that share the same gradient orientation) and curve grow (gather
regions that describe a convex and smooth contour).
'rectangle.c' defines a rectangle structure (i.e. segment with width) to
approximate the result of region grow.
'polygon.c' defines a polygon structure (i.e. collection of rectangles).
'ring.c' defines a (circular or elliptical) ring structure.
'elsdc.c' contains refinement and validation functions for different
types of primitives (ellipse, circle, line segment).
'ellipse_fit.c' contains functions to estimate a circle or an ellipse using
pixels positions and their gradient orienatations.
'iterator.c' functions to count the number of aligned pixels inside a rectangle.
'lapack_wrapper.c' contains wrappers for lapack functions for linear system solve.
'pgm.c' IO functions for pgm image format (the only format supported
currently).
'image.c' defines structures for image representation and functions for
gradient computation.
'gauss.c' defines a Gaussian kernel and contains functions to performs
Gaussian filtering of an image.
'misc.c' contains general-purpose functions and constants definitions.
'svg.c' functions to write the result in svg format.


COMPILATION
'makefile' example of makefile to compile the source code. If the paths
to the libraries are ok, a simple 'make' would compile the
code and produce the executable called 'elsdc'.


EXECUTION
./elsdc imagename runs ELSDc on the image specified by 'imagename'. This
version works only with PGM images. This folder contains the
image 'shapes.pgm' for testing purposes.


OUTPUT
'output.svg' contains the execution result in SVG format. 'shapes_output.svg'
contains the result for the sample image 'shapes.pgm'.
'labels.pgm' after execution, each pixel in this image is labelled with the
label of the primitive to which it belongs.
'out_ellipse.txt' contains the parameters of the detected circular/elliptical
arcs in the form 'label x_c y_c a b theta ang_start ang_end'.
'out_polygon.txt' contains the parameters of the detected line segments, grouped
into polygons, defined through contact points, in the form
'label number_of_points x1 y1 x2 y2 x3 y3 ...'.

In the console, the numbers of features of each type are displayed.
To check the installation, run ./elsdc for 'shapes.pgm' image. The output should be
similar to 'shapes_output.svg', and contain 66 ellipses and 145 polygons, whose
parameters are contained in 'out_ellipse.txt' and 'out_polygon.txt'.
The execution time for this sample image is about 4s on my Dell notebook.


DATASETS
We make available two datasets together with their ground truth for
quantitative evaluation of ellipse detectors:

'Dataset1_SyntheticCircles' Dataset1 consists of 20 images, 500x500 pixels,
containing non-overlapping and overlapping circles. The images are corrupted
with five different levels of Gaussian noise, with five different noise
realisations for each noise level and for each image, resulting in 500 image
instances in total. The file 'coord.txt' contains the ground truth circle
parameters in the form:
'pathToimageName.pgm'
'xcenter1 ycenter1 radius1 xcenter2 ycenter2 radius2 xcenter3 ycenter3 radius3'.
Ten images of pure Gaussian noise are also added (folder 'pureNoise/'), where
all detections are false positives.

'Dataset2_CalibrationPatterns' contains (in folder 'images') 40 natural images
of calibration patterns that were included in Higuchi et al.’s package for
camera calibration
http://www.ri.cmu.edu/research_project_detail.html?project_id=617&menu_id=261.
The patterns contain coplanar disjoint and concentric circles. The ground truth
was obtained by manually labelling the contours belonging to circles and rings
projections. For each image in folder 'images', there is a correponding .txt
file in folder 'ground_truth' with the same name, containing the primitive
parameters in the form:
xcenter ycenter major_axis minor_axis theta.

'Dataset3_RealImages' contains real images that were used to produce the results
from the paper "A Contrario Joint Ellipse and Line Detection".

109 changes: 109 additions & 0 deletions Readme.md~
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ABOUT THIS PROJECT
The source files included in this repository (folder 'src') contain the source
code of ELSDc (Ellipse and Line Segment Detector, with Continuous validation),
described in 'Joint A Contrario Ellipse and Line Detection', by
V. Patraucean, P. Gurdjos, R. Grompone von Gioi; this is the enhanced version
of ELSD, published in
'A Parameterless Line Segment and Elliptical Arc Detector with Enhanced
Ellipse Fitting', V. Patraucean, P. Gurdjos, R. Grompone von Gioi, ECCV2012.

Corresponding author: viorica patraucean vpatrauc@gmail.com

Test online the detector by uploading your own images at
http://dev.ipol.im/~jirafa/ipol_demo/elsdc/ (user: demo, pass:demo).

This program is free software: you can redistribute it and/or modify it under
the terms of the GNU Affero General Public License as published by the Free
Software Foundation, either version 3 of the License, or (at your option) any
later version.

REQUIREMENTS
ELSDc requires CLAPACK/CBLAS library for some linear algebra computations.
Version 3.2.1 was used.


SOURCE CODE FILES (folder 'src')
'main.c' contains the main() function; entry point into the application,
calls IO functions and the detection function.
'curve_grow.c' contains functions for region grow (gather neighbour pixels
that share the same gradient orientation) and curve grow (gather
regions that describe a convex and smooth contour).
'rectangle.c' defines a rectangle structure (i.e. segment with width) to
approximate the result of region grow.
'polygon.c' defines a polygon structure (i.e. collection of rectangles).
'ring.c' defines a (circular or elliptical) ring structure.
'elsdc.c' contains refinement and validation functions for different
types of primitives (ellipse, circle, line segment).
'ellipse_fit.c' contains functions to estimate a circle or an ellipse using
pixels positions and their gradient orienatations.
'iterator.c' functions to count the number of aligned pixels inside a rectangle.
'lapack_wrapper.c' contains wrappers for lapack functions for linear system solve.
'pgm.c' IO functions for pgm image format (the only format supported
currently).
'image.c' defines structures for image representation and functions for
gradient computation.
'gauss.c' defines a Gaussian kernel and contains functions to performs
Gaussian filtering of an image.
'misc.c' contains general-purpose functions and constants definitions.
'svg.c' functions to write the result in svg format.


COMPILATION
'makefile' example of makefile to compile the source code. If the paths
to the libraries are ok, a simple 'make' would compile the
code and produce the executable called 'elsdc'.


EXECUTION
./elsdc imagename runs ELSDc on the image specified by 'imagename'. This
version works only with PGM images. This folder contains the
image 'shapes.pgm' for testing purposes.


OUTPUT
'output.svg' contains the execution result in SVG format. 'shapes_output.svg'
contains the result for the sample image 'shapes.pgm'.
'labels.pgm' after execution, each pixel in this image is labelled with the
label of the primitive to which it belongs.
'out_ellipse.txt' contains the parameters of the detected circular/elliptical
arcs in the form 'label x_c y_c a b theta ang_start ang_end'.
'out_polygon.txt' contains the parameters of the detected line segments, grouped
into polygons, defined through contact points, in the form
'label number_of_points x1 y1 x2 y2 x3 y3 ...'.

In the console, the numbers of features of each type are displayed.
To check the installation, run ./elsdc for 'shapes.pgm' image. The output should be
similar to 'shapes_output.svg', and contain 66 ellipses and 145 polygons, whose
parameters are contained in 'out_ellipse.txt' and 'out_polygon.txt'.
The execution time for this sample image is about 4s on my Dell notebook.


DATASETS
We make available two datasets together with their ground truth for
quantitative evaluation of ellipse detectors:

'Dataset1_SyntheticCircles' Dataset1 consists of 20 images, 500x500 pixels,
containing non-overlapping and overlapping circles. The images are corrupted
with five different levels of Gaussian noise, with five different noise
realisations for each noise level and for each image, resulting in 500 image
instances in total. The file 'coord.txt' contains the ground truth circle
parameters in the form:
'pathToimageName.pgm'
'xcenter1 ycenter1 radius1 xcenter2 ycenter2 radius2 xcenter3 ycenter3 radius3'.
Ten images of pure Gaussian noise are also added (folder 'pureNoise/'), where
all detections are false positives.

'Dataset2_CalibrationPatterns' contains (in folder 'images') 40 natural images
of calibration patterns that were included in Higuchi et al.’s package for
camera calibration
http://www.ri.cmu.edu/research_project_detail.html?project_id=617&menu_id=261.
The patterns contain coplanar disjoint and concentric circles. The ground truth
was obtained by manually labelling the contours belonging to circles and rings
projections. For each image in folder 'images', there is a correponding .txt
file in folder 'ground_truth' with the same name, containing the primitive
parameters in the form:
xcenter ycenter major_axis minor_axis theta.

'Dataset3_RealImages' contains real images that were used to produce the results
from the paper "A Contrario Joint Ellipse and Line Detection".

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