A Contour Detection Method Based on the Synergistic Action of Multi-level Inhibition Zones in the Visual Pathway

Abstract

The invention relates to a contour detection method based on the synergistic effect of multi-level inhibition zones of visual pathways. The present invention first constructs a direction-sensitive outer geniculate neuron array, records the contour direction selected by the outer geniculate body, and calculates the response of the outer geniculate neuron; takes the distance as a factor for the visual input of the classic receptive field and inhibitory area of ​​the outer geniculate neuron Carry out quantitative processing, take the difference between the two as the effective response of the inhibition area, and obtain the synergy parameters through dynamic rectification and power exponent normalization; obtain the visual input of the primary visual cortex through the local window weighted fusion of the response of the outer geniculate neurons, and detect Accurate contour response; calculate the primary visual cortex neuron inhibitory area response to obtain the final contour response. The invention considers the step-by-step refined detection mechanism when neurons at different levels perceive directions in the visual pathway, and simultaneously simulates the synergistic effect of inhibition areas between different levels, which can effectively improve the contour detection performance of natural images.

Description

technical field [0001] The invention belongs to the field of machine vision, and mainly relates to a contour detection method based on the synergistic effect of multi-level inhibition zones of visual pathways. Background technique [0002] Contour detection is one of the important links in the early stage of image understanding or visual analysis. The obtained contour features will effectively express the key visual details after de-redundancy. The difficulty of the contour detection task is mainly manifested in two aspects: over-detection and under-detection. The former is due to the interference of false contours such as texture noise, and the latter is due to the difference in the contour contrast distribution of images. The traditional contour detection method is mainly based on the spatial jump of image information, so mathematical means based on differential or morphological operations are adopted, which can usually achieve good performance when the image quality is go...

AI Technical Summary

Problems solved by technology

However, the traditional method completely ignores the biological neural mechanism in visual perception, so it is difficult to meet the detection performance requirements when faced with complex tasks such as multi-level contour detection.

Although the current contour detection methods based on biological vision mechanism simulate the ability of biological vision to extract image contour features to a certain extent, they pay more attention to a certain level of neurons in the visual pathway when simulating the visual information flow processing process of the visual pathway. The classic receptive field or inhibitory area itself, but ignores the synergistic effect of inhibitory areas between different levels in the visual pathway. This synergistic effect changes the isolation of each level of the visual perception model, and can fully utilize the characteristics of overall synergy. Exploiting the important role played by each level in perception

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