📞 +91-7667918914 | ✉️ ijarcce@gmail.com
IJARCCE Logo
International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 6, ISSUE 5, MAY 2017

Fish Recognition based on HOG Feature Extraction using SVM Prediction

Ms. P. Antony Seba, Ms. S. Rama Subbu Laskhmi, Ms. P. Umamaheswari

DOI: 10.17148/IJARCCE.2017.6554

Abstract: Fish image recognition and prediction is a challenging task. This Paper gives an idea about recognition of fish image using correlation coefficient and then Histogram of oriented Gradient (HOG).Finally the fish images are classified based on their features using Support Vector Machine (SVM).This paper aims to detect which species of fish appears on a fishing boat, based on images captured from boat cameras of various angles and this can be used to prevent fishing of endangered fishes.



Keywords: Histogram of oriented Gradient (HOG), Support Vector Machine (SVM), Fish Recognition.

How to Cite:

[1] Ms. P. Antony Seba, Ms. S. Rama Subbu Laskhmi, Ms. P. Umamaheswari, “Fish Recognition based on HOG Feature Extraction using SVM Prediction,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2017.6554