Expert system segmentation of face images
Robust image analysis of photographs for personal documents has been an important open research problem for many years and the interest has been increased by introduction of electronic personal documents, which contain personal digital photographs. International Civil Aviation Organization (ICAO) has defined a set of recommendations defining minimal quality requirements that personal photographs stored in electronic personal documents must satisfy. Some image quality requirements apply only to certain image regions so exact position and location of the image regions has to be known in advance. In this paper, we propose a new knowledge-based method for segmentation of color personal photographs into five regions: skin, hair, shoulders, background, and padding frame. Prior to application of our method, the input image has to be normalized so that both eyes of a person are at the predefined positions within the image. To the best of our knowledge, no method for analysis of personal document photographs has been published in the literature that performs such segmentation. The proposed method consists of two main steps: (i) mean-shift segmentation step; and (ii) region labeling step based on a rule-based expert system. The most important component of the system is a set of rules specifically developed to enable robust labeling of personal document image regions. Extensive experimental validation has been conducted on four image sets and has demonstrated the accuracy and robustness of the proposed method.
image analysis mean-shift segmentation face image segmentation knowledge-based segmentation