アメリカのコンピューター科学工学ジャーナル の調査 オープンアクセス

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A New Method in Shape Classification Using Stationary Transformed Wavelet Features and Invariant Moments

Arash Kalami

A New Method in Shape Classification Using Stationary Transformed Wavelet Features and Invariant Moments

Representation of the image classification is proposed in this research. The vector calculation defines the population set in image classification. Image classification parameters consists of six lateral information corresponding to the scale stationary in the direction perpendicular to the axis and direction. Here a scale stationary is used due to the wavelet that the use of the normal projection model. Detailed information can be modeled by the scaling stationary of the object, because they are directly cost is defined in grayscale than the sum of the squared wavelet between the images. Template classification and the image classification are categorized in different region of partitioning.