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首页> 外文期刊>Journal of Engineering & Applied Sciences >An Intelligent Image Classifier Based on Histogram of Oriented Gradients Features
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An Intelligent Image Classifier Based on Histogram of Oriented Gradients Features

机译:一种基于面向梯度特征直方图的智能图像分类器

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摘要

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%.
机译:本研究提出了一种基于人工神经网络(ANN)的图像分类的智能分类器。 已使用取向梯度(HOG)Techinque的直方图,以便从图像中提取特征。 ANN监督前馈缩放共轭渐变梯度算法,用于吸引所提出的分类器。 无论大小或颜色图如何,直接处理输入图像以提取矢量特征。 ANN的架构被选中以简单且适当地执行高精度的分类过程。 此工作在CALTECH数据集上执行。 四类图像用于测试和评估所提出的分类器的性能(所有类别的96个图像),测试图像由192个图像组成(每个类别的48个图像)。 实验结果表明,分类率为93.23%。

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