Moving object extraction method based on optical flow method and superpixel division

Abstract

The invention discloses a moving object extraction method based on superpixel division and an optical flow method, and mainly solves the problems of more noises, high-frequency information loss, inaccurate boundary and the like of the existing moving object extraction method. The implementation steps of the method are as follows: (1), inputting an image, and pre-dividing the image into a superpixel set S to obtain a mark sheet I 2; (2), taking images of two adjacent frames in a video sequence and determining a rough position of a moving object by a Horn-Schunck optical flow method; (3), using the optical flow method to obtain the speed u in the horizontal direction and the speed v in the vertical direction, wherein V is speed amplitude of the optical flow method; (4) performing median filtering, Gauss filtering, binarization operation and morphology opening and closing operation on the optical flow result V to obtain V4; (5) using a superpixel division result to further correct the optical flow result, and extracting to obtain the accurate moving object. Superpixels belonging to a moving area are extracted accurately. Simulation experiments show that compared with the prior art, the moving object extraction method has the advantages of simple operation, small noise, clear boundary and the like, and can be used for extracting the moving object in the video sequence.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a moving target extraction based on superpixel segmentation and Horn-Schunck optical flow method, which can be used for target tracking and target detection. Background technique [0002] Moving target extraction refers to the operation of separating the moving target from the background in a single image or a sequence of images, identifying and interpreting meaningful object entities from the image and extracting different image features. According to whether the camera is still or not, motion detection is divided into static background and dynamic background. Most video surveillance systems have fixed cameras, so moving object detection under static background has attracted extensive attention. The commonly used moving target extraction methods include background subtraction method, frame difference method and optical flow method. Background subtraction method: Subtract the for...

AI Technical Summary

Problems solved by technology

[0005] For video surveillance systems, the images used are basically captured by the camera in a static state, so for systems that require real-time and accuracy, it is not practical to use the optical flow method to detect targets purely

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