Deep learning techniques applied to the cattle brand recognition

Abstract

The automatic recognition of cattle brandings is a need of the government organizations responsible for controlling this activity. To help this process, this work presents a method that consists in using Deep Learning techniques for extracting features from images of cattle branding and Support Vector Machines for their classification. This method consists of six stages: (a) selection of a database of images; (b) selection of a pre-trained CNN; (c) pre-processing of the images, and application of the CNN; (d) extraction of features from the images; (e) training and classification of images (SVM); (f) evaluation of the results obtained in the classification phase. The accuracy of the method was tested on the database of a City Hall, where it achieved satisfactory results, comparable to other methods reported in the literature, with 91.94% of Overall Accuracy, and a processing time of 26.766 s, respectively.