The zip file contains the implementation and usage examples of algorithm from  and  for detecting circular objects in a given image.
The algorithm in , called separability filter, computes the Fisher criterion with a circular shape of a mask filter all over the image by sliding window. From the computation of the Fisher criterion, we obtain a separability map where the local peaks are most likely the center of the circular objects. To speed up the computation of , the work of  approximates the shape of circular shape with four combined rectangular shapes and uses Integral image in the computation. For the details please refer to  and .
Please read the included readme.txt file for the description of the files.
A demonstration video can be found at https://youtu.be/NB6AZvOYxC0
 Y. Ohkawa, C. H. Suryanto, K. Fukui, "Fast Combined Separability Filter for Detecting Circular Objects", The twelfth IAPR conference on Machine Vision Applications (MVA) pp.99-103, 2011.
 K. Fukui, O. Yamaguchi, "Facial feature point extraction method based on combination of shape extraction and pattern matching", Systems and Computers in Japan 29 (6), pp.49-58, 1998.
Our homepage: http://www.cvlab.cs.tsukuba.ac.jp/
CVLAB Tsukuba (2023). Separability filter for detecting circular shape (https://www.mathworks.com/matlabcentral/fileexchange/55735-separability-filter-for-detecting-circular-shape), MATLAB Central File Exchange. Retrieved .
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