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Improved Hopfield neural network based recognition method for clothes logo

A technology of neural network and recognition method, which is applied in the field of clothing logo recognition of Hopfield neural network, can solve the problems of low recognition efficiency and achieve the effect of improving efficiency

Inactive Publication Date: 2015-05-13
SICHUAN UNIV
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  • Summary
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Problems solved by technology

[0003] The embodiment of the present invention provides a clothing logo recognition method based on the improved Hopfield neural network to solve the existing problem of extremely low efficiency of manually recognizing commodity logos

Method used

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  • Improved Hopfield neural network based recognition method for clothes logo
  • Improved Hopfield neural network based recognition method for clothes logo
  • Improved Hopfield neural network based recognition method for clothes logo

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Embodiment Construction

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention.

[0032] figure 1 It is a schematic flow chart of the clothing logo recognition method based on the improved Hopfield neural network provided by the embodiment of the present invention. The traditional Hopfield neural network tends to converge to the local extremum, the convergence process is oscillating, the calculation is complex and there is an integral term, which limits the application. The embodiment of the present invention adopts the Hopfield neural network model improved by Li. The improvement is mainly reflected in the energy function using the quadratic term. The improved Hopfield neural network model has more advantages in clothing recognition. This neural...

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Abstract

The embodiment of the invention discloses an improved Hopfield neural network based recognition method for a clothes logo, applies to the field of computers, and aims at solving the problem of extremely low manual recognition efficiency of goods logos in the prior art. The method comprises the steps of extracting characteristics of an original image through wavelet transformation; building a Hopfield neural network model by using the characteristics as the target mode. The method is applied to logo recognition.

Description

technical field [0001] The invention relates to the field of computers, in particular to a clothing mark recognition method based on an improved Hopfield neural network. Background technique [0002] As humans enter the information age, computers are increasingly used in various fields. People often interpret the visual information of clothing through human eyes to determine the color, brand, style and other characteristics of clothing. These characteristics are especially important for occasions where dress codes are specified. For example, PetroChina requires employees to wear red work clothes with company logos. And use this as the standard for passing the access control. Clothing recognition is extremely challenging due to its variability and the complexity of the environment. At present, there are still a lot of gaps in the application research of commodity logo positioning. At present, it mainly relies on manual identification of product logo positioning, which is e...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/54G06N3/02
CPCG06N3/02G06V10/52G06F18/214
Inventor 彭德中章毅吕建成张蕾张海仙桑永胜郭际香毛华甄亮利傅夏生
Owner SICHUAN UNIV
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