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Coin image recognition method based on sparse representation

A sparse representation, image recognition technology, applied in the field of image processing

Inactive Publication Date: 2010-10-27
HANGZHOU DIANZI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In the literature that has been published so far, there is no research on coin image recognition based on sparse representation.

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  • Coin image recognition method based on sparse representation
  • Coin image recognition method based on sparse representation
  • Coin image recognition method based on sparse representation

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Embodiment Construction

[0032] Below in conjunction with embodiment the present invention is further described.

[0033] The coin image recognition method based on sparse representation of the present invention is:

[0034] Step (1) coin image preprocessing

[0035] Obtain the grayscale image of the front and back of the coin (one side of the coin is defined as the front and the other side is the back), and use the existing edge detection technology (such as Sobel, Prewitt, Canny operator, etc.) and the Hough transform circle detection method to determine the coin area. Standardize the size of the coin area to obtain a coin image with a background gray value of 0 and a coin area with a non-zero gray value. The image size is N×N, N=2R, and R is the preset radius of the coin expressed in pixels, such as R= 16. R should not be too large, if it is too large, the number of samples n must be large enough to make equations (3) and (4) meet the conditions of underdetermined equations, and it will greatly i...

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Abstract

The invention relates to a coin image recognition method based on sparse representation. The traditional image recognition method has poor recognition effect. The coin image recognition method comprises the steps of: firstly, obtaining gray level images of the front face and the back face of a coin for preprocessing and determining a coin region, standardizing the size of a coin image; expanding a training sample image into a plurality of angle samples and selecting a main training sample, expressing a testing coin sample into sparse representation of a training sample set, solving an optimal sparse coefficient vector; reconstructing the testing coin image, determining the coin image category by using a reconstructing error; and identifying the coin by utilizing the statistical property of the sparse coefficient vector. The invention can recognize the coin image without extracting the surface characteristics of a coin with rotational invariance, and has simple implementation method.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a method for processing and recognizing coin images, in particular to a coin image recognition method based on sparse representation. technical background [0002] With the popularity of self-service application equipment, more and more occasions require the equipment to have the function of identifying coins, especially the emergence of counterfeit coins and a large number of game coins on the market, which puts forward higher requirements for coin identification. According to the existing literature, there are two main coin identification methods at present: one is to use an oscillating coil to generate an electromagnetic field on the coin path through which the coin passes, and when the coin passes through, an eddy current is generated in the coin, and the eddy current generated in the coin passes through mutual induction with the oscillating coil , cause changes in the...

Claims

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Application Information

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IPC IPC(8): G07D7/20G07D7/202
Inventor 陈华华
Owner HANGZHOU DIANZI UNIV
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