Software and source codes


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Please send an email to me for the source code of any of my published research article. I will try to share it as soon as possible.

[1] Dilip K. Prasad, Maylor K.H. Leung and Chai Quek,ElliFit: An unconstrained, non-iterative, least squares based geometric Ellipse Fitting method,”  Pattern Recognition , vol. 46, issue 5, pp. 1449-1465, 2013. (Matlab Source Code)(OpenCV source code by Harish(dot)Venkatesan[at]colorado(dot)edu)

[2] D. K. Prasad, Maylor K.H. Leung and Siu-Yeung Cho, “Edge curvature and convexity based ellipse detection method,”  Pattern Recognition (Elsevier), vol. 45, issue 9, pp. 3204-3221, 2012.(PDF) (list of 400 Real Images Caltech256)  (Ellipse Labeling Tool)

[3] Polygonal approximation source codes related to following work at Matlab code: OpenCV(C#,VB.Net) code
Dilip K. Prasad, Chai Quek, Maylor K.H. Leung, and Siu-Yeung Cho, “A parameter independent line fitting method,” 1st IAPR Asian Conference on Pattern Recognition (ACPR 2011), Beijing, China, 28-30 Nov, 2011.

[4] Extraction of smooth edge curves(polygonal approximation, sharp turn, inflexion point detection) related to following papers section 2:
Dilip K. Prasad, Maylor K.H. Leung and Siu-Yeung Cho, “Edge curvature and convexity based ellipse detection method,” Pattern Recognition, 2012. (This code contains the steps mentioned in the fig 1(b) of the ellipse detection paper of pattern recognition journal.

[5] Generation of elliptic hypothesis(section 3.1-3.5) related to following papers
Dilip K. Prasad, Maylor K.H. Leung and Siu-Yeung Cho, “Edge curvature and convexity based ellipse detection method,” Pattern Recognition, 2012. (This code contains the steps mentioned in the fig 1(c) of the ellipse detection paper of pattern recognition journal.

[6] Ellipse Labeling Tool used for acquiring ground truth for real images from volunteers.(section 5.2 of 'Edge curvature and convexity based ellipse detection method' paper. 

[7] List of 400 images from Caltech256 dataset used for (section 5.2 of 'Edge curvature and convexity based ellipse detection method' paper)

[8] 199 image annotated dataset from caltech 256 database (Caltech 256 annotated real image ellipse dataset) (sorry, fellow researcher!!! Due to hardware crash I have lost remaining 201 image annotated files).

[9] Source codes for - Dilip K. Prasad, and Michael S. Brown, “Online tracking of deformable objects under occlusion using dominant points,”Journal of Optical Society of America A (OSA), 2013.

[10] Source codes for - Dilip K. Prasad, Maylor K. H. Leung, Chai Quek, and Michael S. Brown, “DEB: Definite error bounded tangent estimator for digital curves,” IEEE Transactions on Image Processing, 2014. (PDF)

[11] Dongliang Cheng, Dilip K. Prasad, and Michael S. Brown, “On Illuminant Estimation:Why spatial domain methods work and the role of the color distribution,” Journal of Optical Society of America A (OSA), vol. 31, issue 5, 2014. (PDF) (Project page and NUS dataset)

[12] Nguyen Rang, Dilip K. Prasad, and Michael S. Brown, “Training-Based Spectral Reconstruction from a Single RGB Image,” European Conference on Computer Vision (ECCV 2014), Zurich, Switzerland, 6-12 Sept, 2014.(PDF)(Source code, dataset,Project page)

[13] Nguyen Rang, Dilip K. Prasad, and Michael S. Brown, “Raw-to-raw: Mapping between image sensor color responses,” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2014), Columbus, Ohio,USA, 24-27 June, 2014.(PDF) (Demo Raw-to-Raw)

[14] Dilip K. Prasad  and Maylor K.H. Leung, “Clustering of Ellipses based on their Distinctiveness: An aid to Ellipse Detection Algorithms”, 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT 2010), Chengdu, China, 9-11 July, 2010.(pdf)(source code)

[15] Dilip K. Prasad and Looi Wenhe, “Metrics and statistics of frequency of occurrence of metamerism in consumer cameras for natural scenes”  Journal of Optical Society America A (OSA),2015.  (NUS Hyperspectral dataset)
[16] Dilip K. Prasad and K. Agarwal, “Classification of hyperspectral or trichromatic measurements of ocean color data into spectral classes”, Sensors (MDPI),  2016.(PDF)(sourcecode , filesize- 590KB) (sourcecode with sample data, filesize - 2.13 GB)