Image segmenting method based on improvement of intersecting visual cortical model

Abstract

The invention discloses an image segmenting method based on improvement of an intersecting visual cortical model. The method comprises the following steps of: firstly improving ICM basic model, establishing a network on the basis of improved ICM basic model, initiating the network parameter, inputting the original image to be segmented, self-adaptively adjusting each parameter in each neuron model according to the self-characteristic of the input image; subsequently updating the internal state value, dynamic threshold and output value of each neuron, outputting the sequentially iterative segmented images, calculating and memorizing the mutual information amount of the original image and the segmented images; and finally judging whether to iterate continuously or output the best segmented image according to the current iterative times. The method simplifies the model, improves the efficiency, completes the segmentation automation, solves the problems that the current model parameter needs to be adjusted manually by test according to different images and the best segmentation needs to be adopted manually, and has more obvious visual advantages simultaneously.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an image segmentation method based on an improved cross visual cortex model. Background technique [0002] Image segmentation is the key content of image analysis, and has been highly valued by researchers at home and abroad for many years. Thousands of various types of segmentation methods have been proposed so far. However, these segmentation methods cannot meet the satisfaction level of human vision in some cases. In recent years, some scholars have proposed a neural network that simulates a biological system by combining the human visual neural perception mechanism with the help of a biological model of the mammalian visual cortex, and obtained a more accurate image segmentation effect. [0003] The Intersecting Cortical Model (ICM) is the product of the crossover of various cortical models. It is mainly evolved from the Eckhorn model and the Rybak model, while extracting oth...

AI Technical Summary

Problems solved by technology

For different images, different parameters need to be selected. At present, the selection of parameters is generally manually set through repeated experiments, which greatly limits the application of ICM-based image segmentation.

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