Journal of Engineering and Applied Sciences

Year: 2018
Volume: 13
Issue: 20
Page No. 8506 - 8510

An Intelligent Image Classifier Based on Histogram of Oriented Gradients Features

Authors : Methaq Talib Gaata and Sahar Muneam

Abstract: This study presents an intelligent classifier for images classification based on Artificial Neural Network (ANN). The Histogram of Oriented Gradients (HOG) techinque has been used in order to extract features from image. The ANN supervised feed-forward scaled conjugate gradient algorithm used to bulid the proposed classifier. The input image is processed directly to extract vector features regardless of size or colour map. The architecture of ANN is selected to be simple and appropriate to carry out the classification process with high accuracy. This work is performed on the Caltech dataset. Four classes of image are used to test and evaluate the performance of the proposed classifier (96 images for all category), the testing images consists of 192 images (48 images for each category). Experimental results showed that the classification rate was 93.23%.

How to cite this article:

Methaq Talib Gaata and Sahar Muneam, 2018. An Intelligent Image Classifier Based on Histogram of Oriented Gradients Features. Journal of Engineering and Applied Sciences, 13: 8506-8510.

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved