Restoring blood vessel patterns and tattoos from JPEG compressed skin images for forensic analysis

Abstract

Using digital evidence images for criminal and victim identification in some legal cases, such as child sexual abuse and masked gunman, can be very challenging, because the faces of criminals or victims are not visible. Blood vessel patterns under human skin and tattoos have been proposed as biometrics to overcome this challenge. However, these images are always taken by consumer cameras and compressed by the JPEG compression method. As a lossy compression method, the JPEG compression method seriously degrades the clarity of the blood vessel patterns and tattoos. To finally utilize blood vessels and tattoos for identifying criminals and victims or searching suspects, overcoming this challenge from the JPEG compression method is essential. Existing methods are not suitable for restoring the blood vessel patterns and tattoos because most of them are designed for generic images and their main targets are to remove the blocking artifacts and improve the visual quality. In this thesis, a skin image analysis and a compression test are performed to study the characteristics of compressed skin images. Then, based on the skin image analysis and the compression test, two skin image restoration algorithms are specially designed to restore blood vessel patterns from compressed images. Finally, an algorithm based on deep learning is proposed to recover tattoo images from their degraded versions. Skin image databases and tattoo image database are constructed for algorithm development. To recover the blood vessel patterns from compressed skin images, a skin image analysis and a compression test are first conducted to find out the critical factors influencing blood vessel pattern quality. The skin image analysis aims to figure out how blood vessel information distributes in the luminance channel (the Y channel) and the chrominance channels (the U and V channels). The compression test is further performed to identify how the lossy operations in the JPEG compression method degrade the blood vessel pattern quality. The down-sampling operation and the quantization operation are examined separately in the test. The importance of the Discrete Cosine Transform (DCT) coefficients is also tested step by step. Based on the analysis, two restoration algorithms are designed to recover blood vessel patterns by estimating the original critical DCT coefficients. I would like to thank all those people who contributed in some way to my Ph.D. study. First and foremost, I would like to express my sincere gratitude to my supervisor Dr. Kong Wai-Kin Adams for his invaluable guidance, selfless support and encouragement during my Ph.D. study. His enthusiasm and rigorous attitude to research inspire me in my study and work. He spends a lot of time and effort to train me to be an independent researcher. And he shares with me his own experience and vision about research which motivate me to reach my own goals as well. Without his guidance and persistent help this thesis would not have been possible. My sincere thanks also go to Dr. Tang Chaoying and Dr. ...