Sleep condition detection method based on mobile phone identification

Abstract

The invention discloses a sleep condition detection method based on mobile phone identification. The sleep condition detection method based on the mobile phone identification comprises the following steps that S1, a mobile phone camera is used for scanning the periphery of a target person to obtain an eye periphery image; S2, the eye periphery image obtained through scanning is analyzed through an identification unit of the mobile phone, and image feature information of under-eye puffiness and a dark circle is obtained; S3, a main control unit of the mobile phone compares the obtained image feature information of the under-eye puffiness and the dark circle with pre-stored related expert information, and the ration between the two types of information is calculated; S4, the obtained ratio is compared with an empirical value, if the ratio is smaller than the empirical value, the sleep condition of the target person is judged to be good; and if the ratio is larger than the empirical value, the target person is judged to have insufficient sleep; and S5, a judged result is output through a mobile phone display unit.

Description

technical field [0001] The invention relates to a method for obtaining the identity information of a fugitive wanted person through a mobile phone. Background technique [0002] Now, the computing power of smartphones is getting stronger and stronger. Smartphones with dual-core processors + independent display units and camera lenses with more than 500W pixels have become popular. The powerful configuration and processing capabilities of modern smartphones have already surpassed those of the mainstream two years ago. PC and mobile phone have become an intelligent mobile Internet terminal, and its expanded functions have already surpassed people's imagination. [0003] Pupil recognition has relatively high requirements for related hardware: processing hardware and imaging equipment. It was only used in computers and high-precision camera systems before. With the development of smart phones, smart phones also have the ability to process pupil images in real time. The populari...

AI Technical Summary

Problems solved by technology

[0004] The pace of modern life is getting faster and faster. Young urban white-collar workers are forced to work overtime due to the heavy pressure of life. In order to complete work on time, overtime work has become commonplace. Insufficient sleep is more common among young white-collar workers today. Many young People who think they are young often ignore their own body warning information, and do not pay enough attention to ordinary body information such as dark circles and puffy bags under the eyes

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