Deep Learning Techniques Applied to the Cattle Brand Recognition

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10657)

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.

Keywords

Deep learning Convolutional neural network Recognition images Support Vector Machines Cattle brand 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Federal University of PampaAlegreteBrazil
  2. 2.Federal University of Santa MariaSanta MariaBrazil
  3. 3.Federal Institute FarroupilhaSanto ÂngeloBrazil

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