Pig Ear Extraction Based On An Improved Active Contour Model

With the integration and scale of pig breeding, the frequency of some diseases is also increasing. To automatically detect porcine reproductive and respiratory syndrome (PRRS) during the pig cultivation process, this article proposes an improved method for pig ear extraction that is based on the active contour model. Firstly, we use the Gaussian scale space filtering and piecewise linear transformation algorithm to highlight the target zones of interest. Secondly, we use a randomly picked ear image point to reconstruct the image region and combine the active contour model to coarse segment the ear image. Finally, by taking advantage of the modified active contour model, the method precisely extracts the pig ear image. The experimental result shows that the proposed method can achieve better segmentation results. The segmentation accuracy of the image of pig contains only one ear can exceed 90%, and the accuracy of the image of pig contains two ears is greater than 85%.