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- W4382119005 abstract "Since long time, skin detection has been primarily required in the detection and tracking of human faces, gesture analysis, content-based image retrieval, and image color balancing applications. In this paper, for the first time, color-based skin detection is applied to segment cattle, particularly cows, in cow images captured from a mobile camera at cow’s natural habitat. A pixel in a cow image is classified as skin and non-skin by using the Bayes classifier with maximum likelihood estimation. The required 2D skin and non-skin color model is formed in HSV color space by considering 16, 32, and 256 bins per channel. The efficacy of the classifier has been tested on manually created and publicly available online database. The evaluation is carried out on the basis of performance metrics such as recall, precision, false positive rate, and false negative rate." @default.
- W4382119005 created "2023-06-27" @default.
- W4382119005 creator A5024327160 @default.
- W4382119005 date "2023-01-01" @default.
- W4382119005 modified "2023-09-24" @default.
- W4382119005 title "Segmentation of Cattle Using Color-Based Skin Detection Approach" @default.
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- W4382119005 doi "https://doi.org/10.1007/978-981-19-8669-7_55" @default.
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