Trademark detection method based on convolutional neural network

A convolutional neural network and detection method technology, applied in the field of target detection and recognition, can solve problems such as inability to apply in daily life, increase in the number of windows, and decrease in recognition rate, achieve good invariance, reduce false detection rate, and improve detection speed. Effect

Inactive Publication Date: 2014-10-01
ZHEJIANG UNIV
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Problems solved by technology

Most of the existing target detection and recognition methods are based on traditional features. When the trademark is affected by angle changes, lighting conditions, and slight deformation, the recognition rate decreases and cannot be applied to daily life.
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  • Trademark detection method based on convolutional neural network
  • Trademark detection method based on convolutional neural network
  • Trademark detection method based on convolutional neural network

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Embodiment Construction

[0023] The invention proposes a trademark detection method based on a convolutional neural network, which trains the convolutional neural network on an already marked trademark sample set. In the process of testing, first select the local area of ​​the test image as a candidate window through the selection of the target area, and use the trained convolutional neural network for identification. figure 1 It is a flow chart of the trademark detection method based on the convolutional neural network of the present invention. like figure 1 As shown, the trademark detection method based on convolutional neural network of the present invention comprises the following steps:

[0024] Step 1. Establish a sample set including various trademark pictures and non-trademark pictures, mark the local area where the trademark is located in the sample, and perform sample preprocessing.

[0025] The present invention uses a convolutional neural network for trademark recognition. According to ...

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Abstract

The invention discloses a trademark detection method based on a convolutional neural network. According to the method, various kinds of trademark pictures and pictures without trademarks are collected, and the pictures with the trademarks are marked; the convolutional neural network is initialized and is trained through trademark samples and non-trademark samples. In the picture testing process, candidate windows which may contain the trademarks in pictures to be tested are selected through a target area selection method, and color space conversion and scaling processing are carried out on the candidate windows; then the candidate windows are input into the convolutional neural network for recognition, and the candidate windows which are recognized to be the trademarks are marked in the pictures to be tested. According to the method, target area characteristic extraction and recognition are combined through the convolutional neural network, uncertainty caused by characteristic design is avoided, besides, good invariability is maintained during rotation, translation and scale changing, detection speed is increased Based on selection of the divided target area, and meanwhile the false detection rate is lowered.

Description

technical field [0001] The invention belongs to the field of target detection and recognition, and relates to a method for detecting a specific target, especially a trademark, from an image. Background technique [0002] At present, with the rapid development of a large number of information media such as TV and the Internet, a large amount of advertising information is flooding people's lives. How to analyze the source of advertisements through the trademarks contained in advertisements and effectively filter the information to ensure the effectiveness of advertisements Sexuality, and the amount of information consumers receive, becomes a matter of concern. [0003] Affected by scale transformation, viewpoint transformation, lighting conditions, occlusion, background interference, etc., accurate detection and recognition of trademarks in complex scenes is a challenging task. Most of the existing target detection and recognition methods are based on traditional features. Wh...

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Application Information

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IPC IPC(8): G06K9/00G06K9/66
Inventor 陈纯张瑞宋明黎阮莹周星辰卜佳俊
Owner ZHEJIANG UNIV
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