Accurate positioning method for human eye on the basis of gray gradation information

A technology of precise positioning and positioning method, applied in the information field, can solve problems such as inability to locate eyes, noise interference, and affect the performance of the face recognition system, and achieve the effect of simple detection method and accurate eye positioning

Inactive Publication Date: 2009-12-30
YUNNAN UNIV
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Problems solved by technology

Generally speaking, the automatic face recognition system mainly includes two parts, namely face detection and face recognition. At present, both parts have some effective methods, although face detection has achieved relatively good results. However, due to the various sizes and different rotation angles of the face, we must normalize the detected face image before performing face recognition. Among the various facial features of the face, the eye

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  • Accurate positioning method for human eye on the basis of gray gradation information
  • Accurate positioning method for human eye on the basis of gray gradation information
  • Accurate positioning method for human eye on the basis of gray gradation information

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Embodiment Construction

[0027] First, use the Adaboost algorithm to perform face detection on the input digital image to obtain the position and size of the face, scale the detected face uniformly to a size of 130×150 pixels, perform grayscale operation on the face image, and select the face A rectangular area with a size of 31×13 pixels in the center of the face image is used as the object of skin color sample analysis. Let I(i, j) be the gray value at (i, j) in the face image, and m be the value of the rectangular area. The average gray value, if m<180, then in the gray histogram of the rectangular area, find the gray value with the most occurrences in the range of [m-10, m+10] as the gray value si of the skin color , use the following formula to enhance the image, and the gray value of the new gray image at (i, j) is denoted as I'(i, j).

[0028] I ′ ( i , j ) = ...

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Abstract

The invention relates to an accurate positioning method for human eye on the basis of gray gradation information, belonging to the technical field of information. The method comprises: (1) human face detection: the area of a human face is positioned from an input image; (2) gray gradation column diagram analysis: gray gradation column diagram analysis is carried out on the human face image to determine the gray gradation range of the complexion area of the human face; (3) image strengthening: gray gradation adjustment is carried out on the image to enable eye characteristics to be more obvious; (4) Gabor wavelet filtration: Gabor wavelet filtration is carried out on the strengthened image, a real part image filtered by Gabor is synthesized to obtain a reference image; (5) cluster analysis: the synthesized reference image is analyzed by using the K-Means cluster method to obtain a binarization human eye candidate window, and the white area in each human eye candidate window after binarization is analyzed to determine the rough position of the human eye, so that the human eye window is obtained; (6) neighbourhood operation: the human eye window is scanned by two neighbourhood operators to determine the canter position of the pupilla. The invention has the advantages of simple detection method and accurate eye positioning.

Description

Technical field: [0001] The invention relates to a method for precise positioning of human eyes based on grayscale information, which belongs to the field of information technology. Background technique: [0002] The construction of automatic face recognition system has become a hot research field in pattern recognition and computer vision. Generally speaking, the automatic face recognition system mainly includes two parts, namely face detection and face recognition. At present, both parts have some effective methods, although face detection has achieved relatively good results. However, due to the various sizes and different rotation angles of the face, we must normalize the detected face image before performing face recognition. Among the various facial features of the face, the eyes It is the preferred feature for face normalization. In face recognition, the accuracy of human eye positioning has an important impact on the effect of face recognition. The existing human ey...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06K9/00
Inventor 钱志明徐丹
Owner YUNNAN UNIV
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