Article antitheft detection method based on visual tag identification

A technology of visual labeling and detection methods, which is applied in the field of image processing, can solve the problems of limited matching accuracy and inability to describe local areas well, and achieve the effect of ensuring accuracy and detection speed

Inactive Publication Date: 2016-05-18
西安三茗科技股份有限公司
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Problems solved by technology

The use of global features is simple and effective, but it cannot describe the local area of ​​the image well, and the matching accuracy is limited

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  • Article antitheft detection method based on visual tag identification
  • Article antitheft detection method based on visual tag identification
  • Article antitheft detection method based on visual tag identification

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Embodiment Construction

[0015] The technical method of the present invention will be further described in detail below. It should be noted that the described embodiments are only intended to facilitate the understanding of the present invention, and have no limiting effect on it.

[0016] The present invention comprises the steps:

[0017] Step 1. Establish a database of visual tags for monitored items.

[0018] (1.1) Collect multiple images of items to be monitored from different angles and under different lighting conditions.

[0019] (1.2) The visual label database is a subset of feature descriptions for items.

[0020] Step 2, extract local features (including but not limited to SIFT features) from the acquired image, and save the extracted local features as a file.

[0021] (2.1) Construct the scale space. The scale space L(x,y,σ) of the image is defined as the convolution operation of the original image I(x,y) and a variable-scale 2-dimensional Gaussian function G(x,y,σ) :

[0022] L(x,y,σ)...

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Abstract

The present invention discloses an article antitheft detection method based on visual tag identification, which performs local feature matching for a frame image extracted from a video and a database image to achieve antitheft detection, thereby improving speed, reliability and accuracy. The article antitheft detection method overcomes the problems that a conventional video article antitheft detection method has low reliability in background modeling and motion segmentation of a video sequence and has a low accuracy in article identification under a complex environment condition. The article antitheft detection method comprises the implementation steps of: (1) extracting local features of a detected article, and establishing a visual tag database; (2) extracting a frame image from a video stream at a fixed time interval; (3) extracting the same local feature, matching the local feature with the local features in the visual tag database, and removing false matching point pairs; and (4) judging whether the number of matching points exceeds a threshold. The article antitheft detection method of the present invention does not need sequence information and only needs a single frame image to perform article antitheft detection, thereby improving detection speed; in addition, local invariant feature matching achieves detection and identification on the condition that the article is partially shielded or illumination changes, thus detection accuracy is ensured.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to computer vision, and in particular relates to image feature extraction and image feature matching, and carries out article anti-theft detection by setting the number of matching point pairs of feature points between images. technical background [0002] Anti-theft of objects is the core function of the video surveillance system. Traditional video-based object anti-theft detection methods usually perform background modeling and motion segmentation on the video sequence, which requires analysis of multiple frames of images. Not only the calculation speed is relatively slow, but also the reliability is low. . When the objects to be monitored are partially occluded, or the image captured by the video changes in illumination, traditional methods cannot accurately identify the objects. [0003] According to the region where feature information is extracted, low-level visual feature...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06T7/00
Inventor 李静赵磊黄韵聂永峰傅俊锋李增胜
Owner 西安三茗科技股份有限公司
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