A Contour Detection Method Based on Orientation Correlation of Multiple Receptive Fields in Visual Pathway

Abstract

The invention discloses a visual pathway multi-receptive-field directional association-based profile detection method. According to the method, classic receptive field characteristics of retinal neurons and non classic receptive field characteristics of LGN (Lateral Geniculate Nucleus) cells in a visual pathway are simulated from spatial scale characteristics of receptive fields of all levels and mutual associativity of receptive fields of the same level in the visual pathway, and rectangular receptive fields of the LGN cells are associated directionally for simulating direction selection characteristics of simple cells of V1 (primary visual cortex). According to the visual pathway multi-receptive-field directional association-based profile detection method proposed by the invention, an important role of visual characteristics in profile detection is brought into full play.

Description

technical field

[0001] The invention belongs to the field of visual neural computing, and mainly relates to a contour detection method based on orientation correlation of multiple receptive fields of visual pathways. Background technique

[0002] Contour is a key attribute of the main object in the image, and its accurate detection is of great significance for improving advanced visual performance such as target recognition and image understanding in the later stage. Usually contour detection needs to accurately locate the target, highlight the continuity of the subject contour, and suppress the background texture edge at the same time. However, in actual scenes, due to the existence of interference factors such as illumination, ghosting, and similarity of texture contours, traditional contour detection methods are difficult to meet the above requirements at the same time. Considering the outstanding recognition and comprehension ability of the visual nervous system, the cu...

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