Fish Detection and Measurement based on Mask R-CNN
Abstract
Morphological measurements of fish, extracted from their contour, are essential indicators, with applications in the fishing industry as well as for monitoring and preserving species. Thus, automatic contour extraction techniques have been explored, and the development of methods for segmenting fish images is necessary. Therefore, the goal of this work was to develop an approach to automatically measure the length of the fish, using the Mask R-CNN network in the fish segmentation task. Comparing the fish length measurements of the proposed method with the size performed manually, an average relative error of only 2.26% was obtained. Thus, a system for automating this process can be faster, more productive, and more scalable.
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