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Foreground automatic extraction method based on multi-view fusion

An automatic extraction and multi-view technology, applied in the field of image processing, can solve the problems of cumbersome foreground extraction process and inaccurate foreground edges, and achieve the effect of accurate foreground extraction results, improved precision, and improved efficiency

Active Publication Date: 2019-12-24
XIDIAN UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to address the above-mentioned deficiencies in the prior art, and propose an automatic foreground extraction method based on multi-view fusion, which is used to solve the foreground problem caused by the existence of human-computer interaction in the existing foreground extraction method based on graph cutting. The extraction process is relatively cumbersome and the technical problem of inaccurate foreground edges caused by limited energy iterative optimization

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[0030] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0031] refer to figure 1 , an automatic foreground extraction method based on multi-view fusion, comprising the following steps:

[0032] Step 1) train the SVM classifier;

[0033] (1a) Collect a sample image set containing foreground categories, and grayscale all the sample images therein to obtain a sample grayscale image set;

[0034] The structure diagram of the sample image set is as follows figure 2 As shown, the sample image set containing foreground includes positive samples, negative samples and sample label files, wherein positive samples are images containing foreground, negative samples are images that do not contain foreground, and the sample label files are positive samples and negative samples. Description of the category and storage location;

[0035] The grayscale of all the sample images in the sample image set ...

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Abstract

The invention proposes an automatic foreground extraction method based on multi-view fusion, which is used to solve the technical problems that the extraction process is cumbersome and the extracted foreground edge is inaccurate in the existing foreground extraction method based on graph cutting. The present invention first trains the SVM classifier, then grayscales the image to be extracted to obtain a grayscale image, detects the sub-image containing the foreground in the gray-scale image through the trained SVM classifier, and uses the sub-image to be extracted The position coordinates in the image are used as the input of the GrabCut algorithm. Foreground extraction is performed on the image to be extracted to obtain the extraction result under the pixel perspective of the image to be extracted. The superpixel image is generated from the image to be extracted with the SLIC algorithm. By fusing the superpixel image and the pixel perspective The following extraction results can be obtained to obtain accurate foreground extraction results of the image to be extracted. The invention can be used for the application and research of stereo vision, image semantic recognition, three-dimensional reconstruction, image search and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to an automatic foreground extraction method based on multi-view fusion. The invention can be used in the application and research of stereo vision, image semantic recognition, image search and the like. Background technique [0002] Foreground extraction is a means to extract objects of interest in an image. It divides the image into several specific regions with unique properties and proposes the technology and process of the target of interest, and has become a key step from image processing to image analysis. The specific explanation is to divide the image into several complementary and overlapping regions according to features such as gray scale, color, texture and shape, and make these features appear similar in the same region, but show obvious differences in different regions. After decades of development and changes, foreground extraction has gradually forme...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/32G06K9/46G06K9/62
CPCG06V10/25G06V10/50G06F18/2411G06F18/253
Inventor 杨淑媛焦李成马宏斌王敏余亚萍刘红英刘志吕文聪赵慧刘振马晶晶马文萍
Owner XIDIAN UNIV
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