SEGMENTATION IN CHICKS IMAGE USING ARTIFICIAL NEURAL NETWORK

A., SenthilRajan (2018) SEGMENTATION IN CHICKS IMAGE USING ARTIFICIAL NEURAL NETWORK. In: Seventh International Conference on Advances in Computing, Communication and Information Technology - CCIT 2018, 27-28 October, 2018, Rome, Italy.

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Abstract

This work proposal is for localization of suspicious noise in chicks images by selecting regions of interest. The presence of salt and pepper noise, speckle noise in an image becomes a difficult task to delimit a lesion. Some techniques of digital processing were applied in 100 chicks images in order to minimize the noise allowing posterior extraction of the contour. The segmentation techniques used to extract the contour was performed by means of the artificial neural network self-organizing map.The various metric evaluation were used to compare the proximity of the automatically obtained area with the manual outline of a animal husbandry, resulting in percent values of 93% to accuracy, 68% to sensitivity and 98% to positive predictive value.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Noise, Speckle, Extraction, Lesion.
Depositing User: Mr. John Steve
Date Deposited: 06 Mar 2019 11:38
Last Modified: 06 Mar 2019 11:38
URI: http://publications.theired.org/id/eprint/43

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