Region detection of lesion area of knee based on colour edge detection and bilateral projection

Wear of the knee is an important indicator of the health status of dairy cows. However, the complex cattle environment and the presence of mud, excrement, and other interferences make examination of the lesion area difficult. We utilised a region detection method based on colour edge detection and bilateral projection to detect the knee area of cows. First, edge information of colour images was obtained by colour edge extraction. Second, most of the background was removed and the leg region was obtained using an open operation, vertical projection, and convex hull processing. Finally, threshold processing and horizontal projection were applied to determine the centre of the target region and the overall target region. To verify the validity of the proposed algorithm, a K-means algorithm and salient region detection were performed. In total, 81 test samples were randomly selected from 300 images, and the results showed that the average overlap rate (OR) was 6.5% and 17.3% higher than that of the K-means and saliency methods, respectively. The false-positive rate (FPR) was 0.8% higher than that of the K-means method and 6.2% lower than that of the saliency method, and the false-negative rate (FNR) decreased by 6.5% and 17.3%, respectively. The present method showed good robustness when background obstructions or ground reflection was present in the images. The results of the present work imply that our method can effectively extract the target region and could stimulate further analysis of cow knees containing swelling and scars.