Vol. 1, Issue 7, Part A (2015)

Abstract
Image compression is currently a prominent topic for both military and commercial researchers. Due to rapid growth of digital media and the subsequent need for reduced storage and to transmit the image in an effective manner Image compression is needed. Image compression attempts to reduce the number of bits required to digitally represent an image while maintaining its perceived visual quality. Biometrics has physiological characteristics means it includes of latent fingerprint recognition and verification and behavioral characteristics means it includes voice and signature. A new fingerprint compression algorithm based on Run-Length Encoding (RLE) with Patch Separation representation is introduced. RLE is based on the idea to replace a long sequence of the same symbol by a shorter sequence and is a good introduction into the image compression field for newcomers. The RLE Finger print compression algorithm first construct a Independent Component Analysis (ICA) Patch Extraction for predefined fingerprint image patches to overcome the dictionary creation. RLE is suited for image compressing any type of Latent fingerprint regardless of its information content, but the content of the data will affect the compression ratio achieved by RLE.