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A face image and image technology, applied in the field of face detection, can solve the problems of high false detection rate and low detection accuracy
Inactive Publication Date: 2016-03-23
SHENZHEN YIHUA COMP +2
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[0004] The purpose of the embodiments of the present invention is to provide a method and device for processing human face images, aiming t
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Embodiment 1
[0042] refer to figure 1 , figure 1 is a schematic flowchart of a method for processing a face image according to an embodiment of the present invention.
[0043] In Embodiment 1, the method for processing a human face image includes:
[0044] Step 101, converting the image to be processed from RGB color space to HSV color space;
[0045] Specifically, the color image collected by the camera is converted from the RGB color space to the HSV color space. In the RGB color space, the three color components all contain brightness information and are correlated, and have poor adaptability to brightness. In the HSV color space, the chroma, brightness, and saturation can be well separated, and there is less overlap with non-skin color points.
[0046] Step 102, acquiring the skin color region of the image to be processed according to the threshold value of the H component in the HSV color space;
[0047] Preferably, the acquiring the skin color area of the image to be processed...
Embodiment 2
[0069] refer to figure 2 , figure 2 It is a schematic diagram of the functional modules of the device for processing human face images according to the embodiment of the present invention.
[0070] In Embodiment 2, the device for processing human face images includes:
[0071] Conversion module 201, for converting the image to be processed from RGB color space to HSV color space;
[0072] Specifically, the color image collected by the camera is converted from the RGB color space to the HSV color space. In the RGB color space, the three color components all contain brightness information and are correlated, and have poor adaptability to brightness. In the HSV color space, the chroma, brightness, and saturation can be well separated, and there is less overlap with non-skin color points.
[0073] The first acquisition module 202 is configured to acquire the skin color region of the image to be processed according to the threshold value of the H component in the HSV color sp...
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Abstract
The embodiment of the invention discloses a method and device of processing face images, comprising: converting a pending image into an HSV color space from an RGB color space; obtaining the skin color area of the pending image according to the H component threshold in the HSV color space; converting the HSV color space into a skin color likelihood image, and performing binary segmentation on the skin color likelihood image; obtaining a face candidate image having a skin color area and a non skin color area separated according to the skin color likelihood image after binary segmentation and the skin color area of the pending image; and marking the skin color area in the face candidate image. The method and device utilize the chroma, brightness and saturation in the HSV color space to perform sound separation, realize less overlapping between skin color points and non skin color points, and improve detection precision; in addition, the method and device utilize an H-SGM skin color model to eliminate the interference of the non skin color area and most background area, and divide a candidate face area so as to realize high face detection precision and less misdetection.
Description
technical field [0001] Embodiments of the present invention relate to the technical field of face detection, and in particular to a method and device for processing a face image. Background technique [0002] As the most basic and important technical link, face detection plays a very important role in the face research area. It is not only the basic step of subsequent face recognition technology, but also has developed into an independent research field with broad application prospects. The current face detection has begun to be widely used in many fields such as new man-machine interface, content-based retrieval, digital video processing, and visual monitoring. [0003] In the existing technical solutions of face detection, a certain skin color model is used alone to detect faces, or a Haar-like feature classifier is used alone to detect faces. Using a certain skin color model alone to detect faces can easily lead to low detection accuracy and high false detection rate. ...
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