Muhammad Tahir1,*, Farhan Riaz2, Imran Usman1,3, Mohamed Ibrahim Habib1
Computer Systems Science and Engineering, Vol.46, No.3, pp. 4007-4022, 2023, DOI:10.32604/csse.2023.032359
Abstract The identification of cancer tissues in Gastroenterology imaging poses novel challenges to the computer vision community in designing generic decision support systems. This generic nature demands the image descriptors to be invariant to illumination gradients, scaling, homogeneous illumination, and rotation. In this article, we devise a novel feature extraction methodology, which explores the effectiveness of Gabor filters coupled with Block Local Binary Patterns in designing such descriptors. We effectively exploit the illumination invariance properties of Block Local Binary Patterns and the inherent capability of convolutional neural networks to construct novel rotation, scale and illumination invariant features. The invariance characteristics of… More >
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