Chin detecting method, chin detecting system and chin detecting program for a chin of a human face

Abstract

A chin detecting method is provided. After detecting a human face and setting a chin detecting window at a lower part of the image, an edge strength distribution is calculated within the chin detecting window and pixels having an edge strength with a threshold value or more are detected based on the edge strength distribution. Then an approximated curve is obtained to most match a distribution of each of the detected pixels and a lowermost part of the approximated curve is identified as the lower base of the chin of the human face. Thereby the chin lower base of the human face can be detected automatically, accurately and quickly.

1 . A chin detecting method for detecting a lower base of a chin of a human face from an image with the human face included therein, the method comprising: 
 detecting a face image of an area including both eyes and lips of the human face but excluding the chin;    setting a chin detecting window with a size including the chin of the human face at a lower part of the detected face image;    detecting pixels having an edge strength with at least a threshold value based on an edge strength distribution by calculating the edge strength distribution within the chin detecting window; and    thereafter obtaining an approximated curve to match a distribution of each of the detected pixels and identifying a lowermost part of the approximated curve as the lower base of the chin of the human face.    
   
   
       2 . A chin detecting method for detecting a lower base of a chin of a human face from an image with the human face included therein, the method comprising: 
 detecting a face image of an area including both eyes and lips of the human face but excluding the chin;    setting a chin detecting window with a size including the chin of the human face at a lower part of the detected face image;    detecting pixels having an edge strength with at least a threshold value by calculating a primary differentiation type edge strength distribution within the chin detecting window and by calculating the threshold value from the primary differentiation type edge strength distribution;    identifying select pixels to be used from the pixels by using a sign inversion of a secondary differentiation type edge; and    thereafter obtaining an approximated curve to match a distribution of the selected pixels by using a least-square method and identifying a lowermost part of the approximated curve as the lower base of the chin of the human face.    
   
   
       3 . A chin detecting method according to  claim 1  wherein the chin detecting window has a horizontally long rectangular shape, a width of the chin detecting window is wider than a width of the human face and a height of the chin detecting window is shorter than a width of the human face.  
   
   
       4 . A chin detecting method according to  claim 2  wherein the primary differentiation type edge strength distribution is obtained by using a Sobel edge detection operator.  
   
   
       5 . A chin detecting method according to  claim 2  wherein the secondary differentiation type edge is obtained by using a Laplace edge detection operator.  
   
   
       6 . A chin detecting method according to  claim 1  wherein the approximated curve is obtained by using a least-square method by a quadratic function.  
   
   
       7 . A chin detecting system for detecting a lower base of a chin of a human face from an image with the human face included therein comprising: 
 an image scanning part for scanning the image with the human face included therein;    a face detecting part for detecting an area including both eyes and lips of the human face but excluding the chin from the image scanned in the image scanning part and for setting a face detecting frame in the detected area;    a chin detecting window setting part for setting a chin detecting window with a size including the chin of the human face at a lower part of the face detecting frame;    an edge calculating part for calculating an edge strength distribution within the chin detecting window;    a pixel selecting part for selecting pixels having an edge strength with at least a threshold value based on the edge strength distribution obtained by the edge calculating part;    a curve approximating part for obtaining an approximated curve to match a distribution of each of the pixels selected in the pixel selecting part; and    a chin detecting part for detecting a lowermost part of the approximated curve obtained in the curve approximating part as the lower base of the chin of the human face.    
   
   
       8 . A chin detecting system according to  claim 7  wherein the pixel selecting part detects pixels having the edge strength with at least the threshold value by calculating the threshold value from a primary differentiation type edge strength distribution calculated in the edge calculating part, and then selects certain pixels to be used from the pixels by using a sign inversion of a secondary differentiation type edge.  
   
   
       9 . A chin detecting program for detecting a lower base of a chin of a human face from an image with the human face included therein making a computer realize the parts of  claim 7 .  
   
   
       10 . A chin detecting program according to  claim 9  wherein the pixel selecting part detects pixels having the edge strength with at least the threshold value by calculating the threshold value from a primary differentiation type edge strength distribution calculated in the edge calculating part, and then selects certain pixels to be used from the pixels by using a sign inversion of a secondary differentiation type edge.