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A Neural Network Approach to Color Image Classification

机译:彩色图像分类的神经网络方法

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摘要

This paper presents a method for image classification by neural networks which uses characteristic data extracted from images. In order to extract characteristic data, image pixels are divided by a clustering method on YCrCb 3-dimensionl-color space and processed by labeling to select domains. The information extracted from the domains is characteristic data (color information, position information and area information) of the image. Another characteristic data, which is extracted by Wavelet transform, is added to the feature and a comparative experiment is conducted. Finally the validity of this technique is verified by means of computer simulations.
机译:本文提出了一种基于神经网络的图像分类方法,该方法使用了从图像中提取的特征数据。为了提取特征数据,通过聚类方法在YCrCb 3维颜色空间上对图像像素进行划分,并通过标记进行处理以选择域。从域中提取的信息是图像的特征数据(颜色信息,位置信息和区域信息)。通过小波变换提取的另一个特征数据被添加到特征中,并进行了对比实验。最后,通过计算机仿真验证了该技术的有效性。

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