Digital image cropping using a blended map

Abstract

In a method and system for mapping a digital image having a plurality of pixels, a skin color map of the digital image is computed. The skin color map has a plurality of skin color values. Each of the skin color values is associated with a respective set of one or more of the pixels. Each of the skin color values indicates a likelihood that the respective pixel set is skin. A face map of the digital image is generated. The face map is divided into one or more face zones and a background exclusive of the face zones. Each of the face zones is a group of the pixels. Each of the face zones indicates a greater likelihood than the background that the respective group of pixels is a face. In the skin color map, the respective skin color values associated with the pixels of the face zones are increased to provide a revised map, which is used in controlling a procedure producing an output.

1 . A method for mapping a digital image having a plurality of pixels, the method comprising the steps of:
 computing a skin color map of the digital image, said skin color map having a plurality of skin color values, each of said skin color values being associated with a respective set of one or more of said pixels, each of said skin color values indicating a likelihood that the respective said pixel set is skin;   generating a face map of the digital image, said face map being divided into one or more face zones and a background exclusive of said face zones, each of said face zones being a group of said pixels, each of said face zones indicating a greater likelihood than said background that the respective said group of pixels is a face;   increasing respective said skin color values associated with the pixels of said face zones to provide a revised map; and   using said revised map in controlling a procedure producing an output.   
   
   
       2 . The method of  claim 1  wherein said generating is independent of said computing. 
   
   
       3 . The method of  claim 1  wherein said increasing further comprises changing respective said skin color values associated with the pixels of said face zones to a maximum likelihood. 
   
   
       4 . The method of  claim 1  wherein said using further comprises:
 segmenting the digital image into a plurality of regions to provide a region map; and   calculating a main subject importance map from said region map and said revised map, said main subject importance map having a plurality of importance values, each of said importance values being associated with a respective said region, each of said importance values indicating a likelihood that the respective said region is of importance to a main subject of the digital image.   
   
   
       5 . The method of  claim 4  wherein said computing and generating are independent of said segmenting. 
   
   
       6 . The method of  claim 5  wherein said generating is independent of said computing. 
   
   
       7 . The method of  claim 4  wherein said segmenting is based on color and lightness. 
   
   
       8 . The method of  claim 4  wherein said calculating further comprises:
 designating each of one or more of said regions as a skin region based on said revised map;   computing at least one geometric feature of each of said skin regions; and   wherein said importance values are based upon said revised map and respective said geometric features.   
   
   
       9 . The method of  claim 8  wherein said geometric features are selected from the group consisting of: a centrality feature and at least one borderness feature. 
   
   
       10 . The method of  claim 4  wherein said using further comprises:
 cropping said digital image without user intervention based on said main subject importance map to provide a cropped digital image; and   outputting said cropped digital image.   
   
   
       11 . The method of  claim 10  further comprising, prior to said cropping:
 determining a main subject using said main subject importance map;   determining one or more face windows, each of said face windows being at least as large as and inclusive of a respective one or more of said face zones;   cropping said digital image to a cropping boundary inclusive of the larger of said main subject and a rectangular area inclusive of all of said face windows.   
   
   
       12 . A computer program product for digital image mapping, the computer program product comprising computer readable storage medium having a computer program stored thereon for performing the steps of  claim 1 . 
   
   
       13 . An automatic digital image mapping system comprising:
 a circuit configured to compute a skin color map of the digital image, said skin color map having a plurality of skin color values, each of said skin color values being associated with a respective set of one or more of said pixels, each of said skin color values indicating a likelihood that the respective said pixel set is skin;   a circuit configured to generate a face map of the digital image, said face map being divided into one or more face zones and a background exclusive of said face zones, each of said face zones being a group of said pixels, each of said face zones indicating a greater likelihood than said background that the respective said group of pixels is a face;   a circuit configured to increase respective said skin color values associated with the pixels of said face zones to provide a revised map; and   a circuit configured to use said revised map in controlling a procedure producing an output.   
   
   
       14 . The system of  claim 13  wherein said circuit configured to increase further comprises a circuit configured to increase respective said skin color values associated with the pixels of said face zones to a maximum likelihood. 
   
   
       15 . A method for mapping a digital image having a plurality of pixels, the method comprising the steps of:
 computing a skin color map of the digital image, said skin color map having a plurality of skin color values, each of said skin color values being associated with a respective set of one or more of said pixels, each of said skin color values indicating a likelihood that the respective said pixel set is skin;   generating a face map of the digital image, said generating being independent of said computing, said face map being divided into one or more face zones and a background exclusive of said face zones, each of said face zones being a group of said pixels, each of said face zones indicating a greater likelihood than said background that the respective said group of pixels is a face;   increasing respective said skin color values associated with the pixels of said face zones to provide a revised map;   segmenting the digital image into a plurality of regions to provide a region map, said segmenting being independent of said computing and generating; and   calculating a main subject importance map from said region map and said revised map, said main subject importance map having a plurality of importance values, each of said importance values being associated with a respective said region, each of said importance values indicating a likelihood that the respective said region is of importance to a main subject of the digital image. cropping said digital image without user intervention based on said main subject importance map to provide a cropped digital image; and   outputting said cropped digital image.   
   
   
       16 . The method of  claim 15  wherein said increasing further comprises changing respective said skin color values associated with the pixels of said face zones to a maximum likelihood. 
   
   
       17 . The method of  claim 16  wherein said calculating further comprises:
 designating each of one or more of said regions as a skin region based on said revised map;   computing at least one geometric feature of each of said skin regions; and   wherein said importance values are based upon said revised map and respective said geometric features.   
   
   
       18 . The method of  claim 17  wherein said geometric features are selected from the group consisting of: a centrality feature and a borderness feature. 
   
   
       19 . The method of  claim 18  further comprising, prior to said cropping:
 determining a main subject using said main subject importance map;   determining one or more face windows, each of said face windows being at least as large as and inclusive of a respective one or more of said face zones;   cropping said digital image to a cropping boundary inclusive of the larger of said main subject and a rectangular area inclusive of all of said face windows.   
   
   
       20 . A computer program product for digital image mapping, the computer program product comprising computer readable storage medium having a computer program stored thereon for performing the steps of  claim 15 .