Data field image feature modeling method adaptive to arbitrary shapes

Abstract

The invention discloses a data field image feature modeling method adaptive to arbitrary shapes. The method includes the steps of construction of data fields in extension-type arbitrary shapes, calculation of a robust data filed distribution feature set, and adaptive feature selection and dimension-reducing modeling; according to the construction of the data fields in extension-type arbitrary shapes, a traditional image data field method is extended, and shape factors are increased, and spatial information contexts of pixels can be taken into full consideration; interaction between pixels located in regions in the same shape is increased, so that the distribution difference of the pixels in the data fields can be decreased, and negative effects of noise pollution and light illumination unenveness can be reduced and eliminated; otherwise, interaction between pixels in regions in different shapes is decreased, and the distribution difference of the pixels in the data fields is increased. According to the calculation of the robust data filed distribution feature set, calculation algorithms include long axis, short axis, eccentricity, field distribution index, weighted field distribution index, local potential variance calculation methods. With the data field image feature modeling method adaptive to arbitrary shapes of the invention adopted, the pixel neighboring ability of detected images is high, and window operation is not needed to be performed on the images.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and relates to an image feature modeling method of an adaptive arbitrary shape data field. Background technique [0002] Image target pattern recognition is one of the important research directions in the field of computer vision, in which feature extraction is the primary key link, and has always been widely concerned by researchers. Product inspection, human-computer interaction and medical diagnosis have also been successfully applied. Feature is an information set that characterizes the essential attributes of image objects, and is the basis for solving problems such as image object recognition. The goal of feature extraction is to obtain a set of small but precise feature quantities, which can reflect the image content independently and completely. The improvement of image spatial resolution enables a large amount of detailed information to be fully represented on the image. Howe...

AI Technical Summary

Problems solved by technology

However, the traditional data field method only implements window operation on the image, and the extracted image features are extremely limited

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