Estimate of the weight in bovine livestock using digital image processing and neural network

A procedure inside the context of artificial vision that estimates the weight in bovine livestock was developed and designed. The input data to the system are images obtained by a videotape camera to color. These images are digitized and preprocessing using filters of elimination of noise; later are implemented and evaluated different segmentation methods that allow to obtain the contour of the animal in semiautomatic form. This process consists of an automatic binarization in its initial stage and an eventual manual adjustment. Later the characteristics that have a strong correlation with the weight of the animal are extracted. These are extracted in a form that is independent of the orientation of the object inside the image. Such characteristics include: the superior area, perimeter, wide of abdomen, wide of haunch, wide of scapula. The estimate of the weight of the animal is made by means of a neural network type feedforward whose inputs feed with the extracted characteristics of the image. Finally the system is evaluated in the number and type of characteristics kept in mind and in the structure of the neural network utilized.