Development of Methods for Crystallogramms Images Classification Based on Technique of Detection Informative Areas in the Spectral Space
نویسندگان
چکیده
We propose a new approach to classifying diagnostic crystallographic images. The classification procedure uses a three-nearest neighbor algorithm based on the Euclidean distance. The image segmentation is conducted in a spatial domain, with energy values in each segment serving as features. Based on the value of the separability criterion used in discriminant analysis, most informative features and their respective segments are selected. With the classification using only informative segments, the classification error is shown to be reduced by 2% when compared with the use of the entire image.
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