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Human eye state recognition method based on graph cut model

A graph cut model and state recognition technology, applied in the field of image recognition, can solve problems such as inability to accurately detect the state of human eyes

Inactive Publication Date: 2014-10-15
张忠伟
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Problems solved by technology

[0009] The purpose of the present invention is to overcome the defects of the above technical problems and solve the problem that the current fatigue detection system cannot accurately detect the state of human eyes (open or closed)

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  • Human eye state recognition method based on graph cut model
  • Human eye state recognition method based on graph cut model
  • Human eye state recognition method based on graph cut model

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Embodiment Construction

[0040] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings. It should be noted that the specific implementation of the human eye state recognition method based on the graph cut model according to the present invention is only an example, but the present invention is not limited to this specific implementation.

[0041] Below in conjunction with accompanying drawing, the present invention is described in detail.

[0042] After the human face is detected in the real-time surveillance video and the eyes are located, the eye picture needs to be processed to identify the opening and closing state of the eyes as the final criterion of fatigue. When processing the eye image, in order to reduce the influence of illumination, etc., firstly use the histogram equalization method to preprocess the eye image to enhance the image contrast; then based on the preprocessed image, construct ...

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Abstract

The invention discloses an image foreground extraction method based on a graph cut model. The method is used for accurate segmentation of a human eye area in an image and belongs to the field of image recognition based on machine vision, and the method is suitable for automatic detection driving fatigue state of a driver. According to the invention, the problem that a present detection system cannot accurately recognize human eye opening and closing states in a complex driving environment is solved. According to the method, a graph cut model is firstly established on an original image; then, based on a segmentation target, an energy function of the graph cut model is constructed; and finally, the function is solved by a max-flow min-cut method so as to obtain the final segmentation result. By the segmentation algorithm, a binary image with a white background and a black eye area is constructed, thus providing stable feature description for follow-up human eye state recognition. It proves validity of the extraction method through experiments. The method provided by the invention can be widely applied in automatic detection of fatigue state of drivers of trains, interurban coaches and ''three danger'' vehicles.

Description

technical field [0001] The invention relates to the field of image recognition based on machine vision, in particular to a method for recognizing human eye states based on a graph cut model, especially an automatic detection method for human eye states (open / closed) in surveillance videos, which is applicable to various Off-line and automatic recognition of the fatigue state of a driver of a large motor vehicle during driving. Background technique [0002] Fatigue driving seriously affects the driver's alertness, adaptability and safe driving ability. According to traffic accident statistics: worldwide, more than 30% of highway traffic accidents are related to driving fatigue, and more than 40% of major traffic accidents in China are directly or indirectly caused by fatigue driving. Therefore, many countries and professional departments are actively carrying out research work on driving fatigue. The detection methods of driver fatigue state can be roughly divided into dete...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/34
Inventor 张忠伟
Owner 张忠伟
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