Movement target detection method based on visual sense bionics

Abstract

The invention proposes a motion target detection method based on vision bionics, which starts from the physiologic structure of a human eye vision system and takes the space-time significant difference feature between a motion target and a background in a sequence image as an entry point. Space frequency and other space features of the sequence image are firstly extracted; and a space significant chart is formed according to the space features. Then, all the significant areas of the former and the latter frames of space significant charts are matched, thus extracting the motion speed of all the significant areas. The space features and the motion features of all the significant areas are carried out the mutual competition, coordination and fusion to form the space-time significant chart under the control by a feature library with the invariable target. After that, the invariable feature of the target in the space-time significant area is extracted. Finally, the evidence theory is adopted to carry out the sequential assumption verification of the invariable feature of the target, thus identifying the motion target. The motion target detection method improves practicality and robustness of the algorithm, which can be widely applied in various types of military and civilian systems, thus having broad market prospect and application value.

Description

Technical field: [0001] The invention belongs to the technical field of moving target detection based on visual bionics, and is a core technology of photoelectric imaging search and tracking systems, precise guidance systems, target monitoring systems, satellite remote sensing systems, safety inspection systems, etc., and is used in various military and civilian systems. can have a wide range of applications. Background technique: [0002] How to solve the identification and stable extraction of moving targets in complex backgrounds has a direct and crucial impact on the performance of photoelectric detection systems. At present, the methods based on motion analysis and feature matching are mainly used for target detection and tracking in complex backgrounds. Due to the complexity and uncertainty of target motion, it is difficult to coordinate the contradiction between the amount of calculation and the reliability of detection and tracking based on motion analysis methods, ...

AI Technical Summary

Problems solved by technology

Relevant data show that the attempts and applications of these visual bionic models have achieved certain results, but their biggest feature is still based on the data-driven selective attention model, lacking the competition, integration and regulation of selective attention and learning, memory and other modules Mechanisms, universality and robustness are still lacking

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