700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ ReadersThis Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Research Article Open Access
In this paper a color descriptor designed for bleeding detection in endoscopic images is proposed. The development of the algorithm was carried out on a representative training set of 36 images of bleeding and 25 clear images. Another 38 bleeding and 26 normal images were used in the final stage as a test set. All of the considered images were extracted from separate endoscopic examinations. The experiments include color distribution analysis in RGB and HSV color spaces, measured over the training set. Next, the color descriptor based on the statistics of pixel values is introduced. The main idea behind the algorithm is to measure the ratios of bleeding and non-bleeding cases for each pixel color value appearing in the training set. Two variants of the descriptor are proposed, first dedicated for exact blood color detection, and second, more lenient, for identifying colors close to bleeding. The experimental evaluation lead to satisfactory results, surpassing the values anticipated basing on the theoretical considerations that were conducted earlier.
computer vision, medical imaging, image processing, image classification, blood detection, Blood Clot Symptoms