Region segmentation for facial image compressing

This paper addresses the segmentation of passport images in order to improve quality of significant regions and to further reduce redundancy of insignificant ones. The approach is to first segment a facial image into two major regions, namely background and foreground. Here a new technique using pixel difference is presented. To compress facial regions at better quality, a face segmentation algorithm is introduced that detects eyes and mouth in a face. Region of interest (ROI) coding is then used to obtain better quality for facial features. At the end, some strategies that make use of region segmentation are proposed in order to increase performance in entropy codin

Compression Of Color Facial Images Using Feature Correction Two-Stage Vector Quantization

A Feature Correction Two Stage Vector Quantization (FC2VQ) algorithm was previously developed to compress gray-scale photo ID pictures. This algorithm is extended to color images in this paper. Two options are compared, which apply the FC2VQ algorithm in RGB and YCbCr color spaces, respectively. The RGBFC2VQ algorithm is found to yield better image quality than YCbCr-FC2VQ at similar bitrate. With the RGB-FC2VQ algorithm, an 128 \Theta 128 24-bit color ID image (49,152 bytes) can be compressed down to 500 bytes with satisfactory quality. 1. INTRODUCTION In a digital ID system, it is desirable to store a photo ID picture along with other personal information such as ID number, other demographic information, and certain biometric information (fingerprint, voice, signature, etc.). To save the storage space, compression of the ID picture is necessary. This is especially important with portable ID devices where the ID information are stored locally in a portable card, e.g., in a barcode o..