DocumentCode :
2512410
Title :
Scale and rotation-invariant feature extraction for color images of iris melanoma
Author :
Danciu, Gabriel ; Banu, Simona Maria ; Ivanovici, Mihai
Author_Institution :
MIV Imaging Venture Lab., Transilvania Univ., Braşov, Romania
fYear :
2012
fDate :
24-26 May 2012
Firstpage :
1436
Lastpage :
1443
Abstract :
This paper proposes a feature extraction approach inspired by the Scale Invariant Feature Transform (SIFT) algorithm. We compute the color gradient based on Principal Component Analysis (PCA). To discover the correct keypoints position, we use the hue information of the image and apply our own color corner detection algorithm, described further in this article. We present our results, both on images of human eye iris affected by melanoma and also on images representing color textures of healthy iris. Then we conclude this paper.
Keywords :
biomedical optical imaging; diseases; eye; feature extraction; image colour analysis; image texture; medical image processing; principal component analysis; transforms; vision defects; PCA; color corner detection algorithm; color gradient; color images; color textures; human eye iris; iris melanoma; principal component analysis; rotation-invariant feature extraction; scale invariant feature transform algorithm; scale-invariant feature extraction; Algorithm design and analysis; Color; Feature extraction; Image color analysis; Malignant tumors; Principal component analysis; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Optimization of Electrical and Electronic Equipment (OPTIM), 2012 13th International Conference on
Conference_Location :
Brasov
ISSN :
1842-0133
Print_ISBN :
978-1-4673-1650-7
Electronic_ISBN :
1842-0133
Type :
conf
DOI :
10.1109/OPTIM.2012.6231886
Filename :
6231886
Link To Document :
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