Determining composition of grain textures by texture classification based on feature distributions

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.