Automatic cattle muzzle print classification system using multiclass support vector machine. (2015)

• Record Type: Journal Article
• Authors: Mahmoud, Hamdi A.; Hadad, Hagar Mohamed Reda El
• Is Part Of: International journal of image mining. Volume 1:Number 1(2015)
• Page Start: 126
• Page End: 140
• Publication Date: 2015
• Subjects: muzzle classification -- image processing -- support vector machines -- multiclass SVM -- box-counting -- histogram equalisation -- cattle muzzles -- biometrics -- feature extraction -- preprocessing -- morphology filtering -- image contrast -- noise removal -- muzzle images -- feature matching -- cattle traceability -- food safety; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

Abstract

Cattle muzzle classification can be considered as a biometric identifier to maintain the livestock and guarantee the safety of cattle products. This paper presents a muzzle-based classification system using multiclass support vector machines (MSVMs). The proposed MSVMs system consists of three phases; namely preprocessing, feature extraction and classifications. Preprocessing techniques, histogram equalisation and mathematical morphology filtering have been used to increase image contrast and removing noise respectively. The proposed system uses box-counting algorithm for detecting feature of each muzzle image. For a strong classification system and achieving more accurate classification result, MSVMs has been used. The experimental evaluation prove the advancement of the presented system as it achieve 96% classification accuracy in case of increase number of classified group to ten groups compared to 90% classification accuracy achieved by traditional classification system.