Research of Data Hiding Techniques in Vector Quantification Domain

• Main Authors: Mei-Chun Chuang, 莊梅君
• Other Authors: Chin-Feng Lee
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/93225721708128686988

碩士 === 朝陽科技大學 === 資訊管理系碩士班 === 98 === By the rapid development of the Internet and the arrival of the digital era, the data encryption becomes more and more important. To enhance the security of data transfer, many scholars have proposed a lot of techniques of information hiding. The techniques which are applied in the spatial, frequency and compressed domain, example for Least Significant Bit Replacement (LSB Replacement) of the spatial domain, Discrete Cosine Transform (DCT) of the frequency domain, vector quantization (VQ) and side match vector quantization (SMVQ) of the compressed domain. To decrease the usage of Internet bandwidth and lower the size of multimedia files, we proposed two techniques related to VQ and SMVQ method to embed the secret message in the compressed domain. In the research, we proposed two data hiding techniques based on the compressed domain. In Exploiting Modification Direction (EMD) scheme, the pixel is only modified as 1 to embed secret data in the cover image. Therefore, the stego-image quality presented high visual quality by the scheme. After sorting results of the codebook for the compressed domain, the codeword of index table resembles the character of neighbor others. Then our proposed scheme embedded the secret data to index table, the codeword of index table adds or subtracts one. After extracting the secret data and using the sorting codebook to decode the stego-image. The decoded image kept a good image quality. Wu et al. proposed block prediction scheme that had high embedding capacity. If increasing the secret message, the stego-image quality will become worse. The second scheme proposed in our research is called “An embedding technique based upon block prediction and code cascading shift”. This method increased the embedding capacity, and recovered the image quality of the decoded image after extracting the secret data. The proposed scheme set the variable threshold to divide into five types and embedded the secret message by SMVQ in the compressed domain, then hiding more and more secret data by code cascading shift method in the embedded blocks. The experimental results show the embedding capacity of the proposed scheme is better than Wu et al.’s scheme. Furthermore, the stego-image kept a high image quality.