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Rapid and high-efficiency near-duplicate image matching method

A technology of approximate repetition and matching method, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of slow image matching speed, large noise, slow extraction speed, etc., achieve noise insensitivity, overcome quantization error, The effect of improving performance

Active Publication Date: 2015-04-08
长安通信科技有限责任公司
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Problems solved by technology

[0005] Aiming at technical problems such as slow extraction of local feature points, high noise, hard quantization of words, and slow image matching speed in the existing bag-of-words model technology, the purpose of the present invention is to provide a fast and efficient approximate repetitive image matching method

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  • Rapid and high-efficiency near-duplicate image matching method

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Embodiment Construction

[0034] In order to make the purpose, technical solutions and advantages of the present invention clearer, the following in conjunction with specific examples, and with reference to the appended figure 1 , to further describe the present invention in detail.

[0035] Execution environment of the present invention adopts a Pentium 4 computer with 2.4G Hz central processing unit and 8G byte internal memory and has compiled the algorithm program of fast and efficient approximate image matching with C++ language, can also adopt other execution environments, not here Let me repeat.

[0036] figure 1 It is a flow chart of a method for approximately repeating image matching in the present invention, comprising the following steps:

[0037] Step 1: Extract the local features of each image in the training image library and perform nonlinear mapping to build a visual vocabulary;

[0038] The local feature mentioned in step 1 refers to the ORB (ORiented Brief) feature, and the ORB feat...

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Abstract

The invention discloses a rapid and high-efficiency near-duplicate image matching method. The method comprises the steps that 1) the ORB characteristic of each image in a training image library is extracted and nonlinear mapping is performed on the ORB characteristic of each image so that a visual word table of the training image library is constructed; 2) sparse coding is performed on the nonlinear mapping ORB characteristic of each image in the training image library by utilizing locally-constrained linear coding according to the constructed visual word table; 3) the ORB characteristic of the image to be matched is extracted and nonlinear mapping is performed on the ORB characteristic of the image to be matched, and then sparse coding is performed on the nonlinear mapping ORB characteristic of the image to be matched according to the constructed visual word table; and 4) similarity of sparse coding of the image to be matched and sparse coding of the images in the training image library is calculated, and if similarity exceeds the preset threshold value, matching succeeds, or matching fails. Reconstruction error of a hard quantification method is reduced so that matching speed is greatly enhanced and the method can be used for real-time matching.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to an approximate image matching (Near-Duplicate Image Match) method. Background technique [0002] With the rapid development of multimedia technology and modern information processing technology, especially the promotion of large-scale mobile applications such as cloud computing, WeChat, and Weibo, the number of images / videos is growing explosively, which inevitably leads to a large number of approximations Repeated images bring great inconvenience to information storage and user retrieval. Therefore, near-duplicate image matching has attracted the interest of some scholars. Through the research of approximate duplicate image matching, on the one hand, image copyright protection can be realized; secondly, in image search engines, it can be used to filter out duplicate images in retrieval results, thereby improving the user’s retrieval quality; in addition, in content-based sensitiv...

Claims

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Application Information

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IPC IPC(8): G06K9/64G06K9/46
CPCG06V10/462G06F18/23213
Inventor 李莉戴帅夫刘丙双
Owner 长安通信科技有限责任公司
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