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Weak and small moving target detection method based on superpixel adjacent frame feature comparison

A feature comparison and moving target technology, applied in the field of image processing, can solve the problems of high false alarm rate and low detection efficiency

Active Publication Date: 2020-03-24
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0005] Aiming at the problems of high false alarm rate and low detection efficiency in most existing detection methods of weak and small moving targets in visible light sequence images, the present invention uses a method based on superpixel graph theory segmentation and comparison of adjacent frame superpixel features to detect visible light images. small athletic target

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  • Weak and small moving target detection method based on superpixel adjacent frame feature comparison
  • Weak and small moving target detection method based on superpixel adjacent frame feature comparison
  • Weak and small moving target detection method based on superpixel adjacent frame feature comparison

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Embodiment Construction

[0041] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0042] The present invention proposes a weak and small moving target detection method based on superpixel adjacent frame feature comparison, comprising the following steps: Step 1: using the SLIC algorithm (simple linear iterative cluster, simple linear iterative clustering algorithm) for the target frame image to realize superpixel segmentation ; Step 2: According to the adjacency relationship of superpixels, generate a graph theory model, design superpixel features, calculate the feature difference between each superpixel, use the feature difference as the boundary value in the graph theory model, and use the graph segmentation algorithm to realize Potential target extraction; step 3: compare the color features of adjacent frames in the potential target area, and if the color feature difference exceeds the set threshold, it will be marked as a moving target.

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Abstract

The invention relates to a weak and small moving target detection method based on superpixel adjacent frame feature comparison. The method comprises the following steps of: 1, performing super-pixel segmentation on a target frame image by using an SLIC (simple linear iterative clustering) algorithm; 2, generating a graph theory model according to the adjacency relation of the superpixels, designing superpixel features, calculating feature differences among the superpixels, taking the feature differences as edge values in the graph theory model, and realizing potential target extraction by utilizing a graph segmentation algorithm; and 3, performing adjacent frame color feature comparison on the potential target area, and if the color feature difference exceeds a set threshold, marking the potential target area as a moving target. According to the method, inter-frame search is avoided, and the efficiency of detecting the weak and small moving target is improved.

Description

technical field [0001] The invention relates to a weak and small moving target detection method based on superpixel adjacent frame feature comparison, and belongs to the technical field of image processing. Background technique [0002] Weak and small moving target detection is an important research topic in the field of image processing and machine vision. Objects of interest and motion in image sequences or videos are distinguished and extracted from the background. In recent years, with the development of drones, the demand for security monitoring of drones has gradually increased, so how to realize weak and small moving target detection has become one of the research hotspots. [0003] Zhu Xuan ("Moving Target Detection Based on Continuity Constrained Background Model Subtraction", Computer Science, 2019, 06, 311-315) proposed a low-rank decomposition background update model with temporal continuity constraints, and applied it to the background model Subtractive video ...

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Application Information

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IPC IPC(8): G06T7/215G06T7/11G06T7/136G06T7/90
CPCG06T7/215G06T7/11G06T7/136G06T7/90
Inventor 王靖宇张国俊王霰禹赵越苏雨张科王震
Owner NORTHWESTERN POLYTECHNICAL UNIV
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