Tattoo image classification method based on deep learning

A classification method and deep learning technology, applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve the problems of low reliability, low realization efficiency, low operation efficiency, etc. Effect

Active Publication Date: 2014-08-20
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0022] In order to overcome the shortcomings of the existing tattoo image classification methods, which are easily affected by the direction of irradiation, skin color, hair, light, image quality, etc., have low reliability, and low implementation efficiency, the present invention proposes a method based on deep learning. Tattoo image classification method, which relies on a super large sample set, pre-processes the image

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  • Tattoo image classification method based on deep learning
  • Tattoo image classification method based on deep learning

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[0039] The present invention will be further described below in conjunction with the drawings.

[0040] Reference Figure 1 ~ Figure 2 , A tattoo classification method based on deep learning, that is, semantic labeling of input tattoo images. The tattoo classification method includes the following steps:

[0041] 1) Sample transformation

[0042] 1.1) Affine transformation

[0043] 1.2) Flexible transformation

[0044] 1.3) Whitening

[0045] 2) Use an autoencoder to perform unsupervised training on color tattoo images, the purpose is to find out the edges, corner information in the tattoo images, and the underlying information shared by these images.

[0046] 3) The result of using the autoencoder is used to initialize the convolutional network template, and the convolutional network uses DropConnect and random pooling.

[0047] The tattoo classification method based on deep learning of this embodiment specifically includes the following steps:

[0048] 1) Sample transformation

[0049] Sin...

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Abstract

The invention discloses a tattoo image classification method based on deep learning. The tattoo image classification method based on the deep learning comprises the following steps: 1) transforming samples: 1.1) affine transformation, 1.2) elastic transformation, 1.3) sheltering simulation and 1.4) whitening; 2) carrying out self-encoding pre-training: training a great quantity of colorful tattoo images by a self-encoding learning machine which is optimized by CUDA (compute unified device architecture) to obtain certain common edge information of the tattoo images, and meanwhile, picking up and applying the images to the first layer of a convolutional network; 3) carrying out convolutional network training to a transformed sample by a result obtained by self encoding. The image classification method based on the deep learning, which is disclosed by the invention, is effectively free from the influence by irradiation direction, skin color, hair, ray, image quality and the like, and has the advantages of good reliability and high realization efficiency.

Description

Technical field [0001] The invention relates to the technical fields of image processing and pattern recognition, in particular to a tattoo image classification method. Background technique [0002] The research on tattoo image recognition has just started, and there are no domestic related papers and patents. In foreign countries, only a few scholars such as A.K. Jain are engaged in tattoo-related academic research. Although there have been certain developments, there are still many problems that need to be solved urgently. First, the existing methods for detecting regions of interest have certain defects. The detection of the interest area of ​​existing tattoo images is mainly through manual calibration or image segmentation algorithms. The image segmentation algorithm is an estimation of the actual interest of users by low-level visual features, and it is difficult to achieve an objective description of the area of ​​interest. Therefore, both methods have subjective issues....

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Application Information

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IPC IPC(8): G06K9/66
Inventor 张永良肖健伟高思斌肖刚
Owner ZHEJIANG UNIV OF TECH
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