Multi-view fusion-based image foreground automatic extraction method

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

Inactive Publication Date: 2018-05-29
西安电子科技大学昆山创新研究院 +1
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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 image foreground automatic extraction method based on multi-view fusion, which is used to solve the problems caused by the existenc

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Embodiment Construction

[0025] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0026] refer to figure 1 , an image foreground automatic extraction method based on multi-view fusion, comprising the following steps:

[0027] Step 1, train the SVM classifier.

[0028] (1a) Collect a sample image set containing foreground categories, and grayscale all the sample images therein to obtain a sample grayscale image set;

[0029] The structure diagram of the sample image set with foreground category is as follows figure 2 As shown in , it contains positive samples, negative samples, and sample label files, where positive samples are images that contain foreground, negative samples are images that do not contain foreground, and sample label files are used to classify and store positive samples and negative samples. illustrate;

[0030] The grayscale of all the sample images in the sample image set is to carry out wei...

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Abstract

The invention discloses a multi-view fusion-based image foreground automatic extraction method. The invention mainly aims to solve the problems of misellaneous extraction processes and the inaccuracyof extracted foreground edges in the prior art. According to the method provided by the technical schemes of the invention, an SVM classifier is trained at first, then the grayscale image of an imageto be extracted is obtained; a sub-image containing a foreground is detected from the grayscale image through the trained SVM classifier; the position coordinates of the sub-image in the image to be extracted are used as the input of the GrabCut algorithm, and foreground extraction is performed on the image to be extracted, and the extraction result of the image to be extracted is obtained from apixel view; an image of the image to be extracted from a superpixel view is generated with the SLIC algorithm; and the image from the superpixel view and the extraction result from the pixel view arefused, so that the foreground extraction result of the image to be extracted is obtained. With the method of the invention adopted, a foreground extraction process can be simplified, and the efficiency and precision of extraction are improved. The method can be used for stereo vision, image semantic recognition, three-dimensional reconstruction and image search.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to an image foreground automatic 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, etc. 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 formed ...

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Application Information

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IPC IPC(8): G06K9/32G06K9/34G06K9/46G06K9/62G06T3/40
CPCG06T3/4053G06V10/25G06V10/267G06V10/44G06F18/2321G06F18/2411
Inventor 王敏马宏斌侯本栋
Owner 西安电子科技大学昆山创新研究院
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