首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >DETERMINING COMPOSITION OF GRAIN MIXTURES BY TEXTURE CLASSIFICATION BASED ON FEATURE DISTRIBUTIONS
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DETERMINING COMPOSITION OF GRAIN MIXTURES BY TEXTURE CLASSIFICATION BASED ON FEATURE DISTRIBUTIONS

机译:基于特征分布的纹理分类确定谷物混合物的组成

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摘要

Texture analysis has many areas of potential application in industry. The problem of determining composition of grain mixtures by texture analysis was recently studied by Kjell. He obtained-promising results when using all nine Laws' 3x3 features simultaneously and an ordinary feature vector classifier. In this paper the performance of texture classification based on feature distributions in this problem is evaluated. The results obtained are compared to those obtained with a feature vector classifier. The use of distributions of gray level differences as texture measures is also considered.
机译:纹理分析在工业中具有许多潜在的应用领域。 Kjell最近研究了通过纹理分析确定谷物混合物组成的问题。当同时使用所有9个Laws的3x3特征和普通特征向量分类器时,他获得了令人鼓舞的结果。本文评估了基于特征分布的纹理分类性能。将获得的结果与使用特征向量分类器获得的结果进行比较。还考虑了使用灰度差的分布作为纹理度量。

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