DocumentCode :
1356264
Title :
Perceptual Segmentation: Combining Image Segmentation With Object Tagging
Author :
Bergman, Rebecca ; Nachlieli, H.
Author_Institution :
Hewlett-Packard Labs., Haifa, Israel
Volume :
20
Issue :
6
fYear :
2011
fDate :
6/1/2011 12:00:00 AM
Firstpage :
1668
Lastpage :
1681
Abstract :
Human observers understand the content of an image intuitively. Based upon image content, they perform many image-related tasks, such as creating slide shows and photo albums, and organizing their image archives. For example, to select photos for an album, people assess image quality based upon the main objects in the image. They modify colors in an image based upon the color of important objects, such as sky, grass or skin. Serious photographers might modify each object separately. Photo applications, in contrast, use low-level descriptors to guide similar tasks. Typical descriptors, such as color histograms, noise level, JPEG artifacts and overall sharpness, can guide an imaging application and safeguard against blunders. However, there is a gap between the outcome of such operations and the same task performed by a person. We believe that the gap can be bridged by automatically understanding the content of the image. This paper presents algorithms for automatic tagging of perceptual objects in images, including sky, skin, and foliage, which constitutes an important step toward this goal.
Keywords :
image segmentation; object detection; JPEG artifacts; automatic tagging; color histograms; image segmentation; low-level descriptors; noise level; object detection; object tagging; perceptual segmentation; photo applications; segment detection; Algorithm design and analysis; Image color analysis; Image segmentation; Pixel; Skin; Snow; Tagging; Image analysis; image segmentation; image tagging; perceptual segmentation; Algorithms; Artificial Intelligence; Documentation; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Visual Perception;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2010.2088970
Filename :
5605666
Link To Document :
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