基于SVM分类器统计特征的水果分类

R. Kumari, V. Gomathy
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引用次数: 18

摘要

水果分类自动化是计算机视觉的一个有趣的应用。基于强度对水果进行分类的计算机视觉策略。,颜色。形状和纹理特征。本文提出了一种利用颜色和纹理特征对水果进行分类的传统方法。传统的水果分类方法依赖于基于视觉能力的人工操作。基于小波变换的统计特征和共现特征,采用支持向量机分类器进行分类。该系统的分类准确率为95.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fruit Classification using Statistical Features in SVM Classifier
Automation of fruit classification is an interesting application of computer vision. The computer vision strategies used to classify a fruit based on intensity., color., shape and texture feature. This paper proposes a traditional technique which uses color and texture feature for fruit classification. Traditional fruit classification method depends on manual operation based on visual ability. The classification is done by Support Vector Machine (SVM) classifier based on statistical and co-occurence features derived from the wavelet transform. The classification accuracy for the proposed system is 95.3%.
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