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Knowing Your Dog Breed: Identifying a Dog Breed with Deep Learning

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Abstract

Dog breed identification is essential for many reasons, particularly for understanding individual breeds’ conditions, health concerns, interaction behavior, and natural instinct. This paper presents a solution for identifying dog breeds using their images of their faces. The proposed method applies a deep learning based approach in order to recognize their breeds. The method begins with a transfer learning by retraining existing pre-trained convolutional neural networks (CNNs) on the public dog breed dataset. Then, the image augmentation with various settings is also applied on the training dataset, in order to improve the classification performance. The proposed method is evaluated using three different CNNs with various augmentation settings and comprehensive experimental comparisons. The proposed model achieves a promising accuracy of 89.92% on the published dataset with 133 dog breeds.

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Acknowledgments

This research was supported by the Royal Golden Jubilee (RGJ) Ph.D. Programme under the Thailand Research Fund (No. PHD/0053/2 561)

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Authors and Affiliations

  1. Faculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, 73170, Thailand

    Punyanuch Borwarnginn, Worapan Kusakunniran, Sarattha Karnjanapreechakorn & Kittikhun Thongkanchorn

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  1. Punyanuch Borwarnginn
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  2. Worapan Kusakunniran
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  3. Sarattha Karnjanapreechakorn
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Corresponding author

Correspondence to Worapan Kusakunniran.

Additional information

Punyanuch Borwarnginn received the B. Sc. degree in information and communication technology from Mahidol University, Thailand in 2009, and the M. Sc. degree in informatics from the University of Edinburgh, UK in 2011. She is currently a Ph. D. degree candidate in computer science from Faculty of Information and Communication Technology, Mahidol University, Thailand.

Her research interests include image processing, biometrics, computer vision, pattern recognition and machine learning.

Worapan Kusakunniran received tee B.Eng. degree in computer engineering from the University of New South Wales (UNSW), Australia in 2008, and the Ph. D. degree in computer science and engineering from UNSW, in cooperation with the Neville Roach Laboratory, National ICT Australia, Autraaha in 2013. He is currently a lecturer with Faculty of Information and Communication Technology, Mahidol University, Thailand. He is the author of several papers in top international conferences and journals. Dr. Kusakunniran served as a program committee member for many international conferences and workshops. Also, he has served as a reviewer for several international coherences and journals, such as International Conference on Pattern Recognition, IEEE International Conference on Image Processing, IEEE International Conference on Advanced Video and Signal Based Surveillance, Pattern Recognition, IEEE Transactions on Image Processing, IEEE Transactions on Information Forensics and Security, and IEEE Signal Processing Letters.

His research interests include biometrics, pattern recognition, medical image processing, computer vision, multimedia, and machine learning.

Sarattha Karnjanapreechakorn received the B. Sc. degree in electrical-mechanical manufacturing engineering from Kasertsart University, Thailand in 2015, and the M. Sc. degree in game technology and gamification from Mahidol University, Thailand in 2017. He is currently a Ph. D. degree candidate in computer science of Faculty of Information and Communication Technology, Mahidol University, Thailand.

His research interests include image processing, biometrics, computer vision, pattern recognition and machine learning.

Kittikhun Thongkanchorn received the B. Sc. degree in information and communication technology from University of Mahidol, Thailand in 2007, and the M. Sc degree in computer science from Faculty of ICT, Mahidol University, Thailand in 2012. He is currently a computer scientist, senior professional level with Faculty of ICT, Mahidol University, Thailand. His research interests include computer system and network, elastic computing and distributed system, computer security and policy, image processing and machine learning.

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Borwarnginn, P., Kusakunniran, W., Karnjanapreechakorn, S. et al. Knowing Your Dog Breed: Identifying a Dog Breed with Deep Learning. Int. J. Autom. Comput. 18, 45–54 (2021). https://doi.org/10.1007/s11633-020-1261-0

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  • DOI: https://doi.org/10.1007/s11633-020-1261-0

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