Enhancing the accuracy of area extraction in machine vision-based pig weighing through edge detection.

Abstract

The accuracy of extracting projected pig area is critical to the accuracy of the weight measurement of pigs by machine vision. The capability of both the conventional and the edge detection methods for extracting pig area was examined using the images of 47 pigs of different weights. Relationship between the threshold value and the extracted area was numerically analyzed for both methods. It was found that the accuracy of the conventional method depended heavily on the threshold value, while choice of threshold value in the edge detection approach had no influence on the extracted area over a wide range. In normal lighting conditions, both methods yielded comparable values of predicted weight; however, under variable light intensities, the edge detection method was superior to the conventional method, because the former was proven to be independent of light intensities. This makes edge detection an ideal method for area extraction during the walk-through weighing process where pigs are allowed to move around. Keywords: Area extraction, edge detection, threshold value, pig weighing, machine vision, image processing DOI: 10.3965/j.issn.1934-6344.2008.01.037-042 Citation: Wang Y, Yang W, Walker L, Rababah T M. Enhancing the accuracy of area extraction in machine vision-based pig weighing through edge detection. Int J Agric & Biol Eng. 2008; 1(1): 37