An automatic splitting method for the adhesive piglets’ gray scale image based on the ellipse shape feature

• A prototype system for piglets average weight monitoring system based on WMSN.
• Split adhesive piglets based on ellipse fitting.
• Apply chain code to determine concave points.
• 5 ellipse combination rules are proposed to merge ellipses.
• Count adhesive piglets automatically for gray scale images.

The average weight of piglets in lactation can be monitored automatically by piglets’ average weight monitoring systems which are designed based on wireless multimedia sensor networks. Piglets counting in an automatic manner for piglets images is the foundation of these systems. Adhesive piglets may exist in an image due to the social character of piglets, which challenges the image splitting and automatic piglets counting.This paper proposes a segmentation algorithm for adhesive piglets images based on ellipse fitting method. Firstly, ellipse fitting is implemented for a large number of images which have one piglet. Parameters range of ellipses fitted by images with a single piglet on different age is extracted. Secondly, contours of connected components in an adhesive piglets image are extracted. Each contour is segmented based on concave points. Ellipse fitting is implemented for each contour segment. Finally, 5 rules for ellipse merging are put forwarded, which are used to merge anomalous ellipses. After ellipse merging, the number of ellipses equals the number of piglets. The proposed algorithm is applied to adhesive piglets images in Matlab R2012b and the experimental results show that the counting accuracy exceeds 86% when the number of piglets is less than 7. The algorithm provides the foundation for the piglets’ average weight monitoring systems.