Data Hiding Method in Color Image Based on Grouping Palette Index by Particle Swarm Optimization with K-means Clustering

We propose a data hiding method in color image with its image palette. Many authors usually embed data into the palette or into the index table of the palette directly. Those data hiding methods embedded the secret data into palette itself, the palette will be changed to a different one. It becomes more difficultly to reveal the embedded information. We apply the particle swarm optimization method with K-means clustering to divide the color image palette into several groups. The largest numbers of pixels of a palette group has, the more data may be embedded in the pixel that falls in this group. In each candidate embedding pixel we check it belongs which group, then we know how many bits can be embedded, due to the number of group members we are going to use is power of two. The current embedding pixel will be replaced by the same group of pixel in the order of embedding data value. The extraction method firstly groups of the pixels of stego-image, and check the pixels to find which group has. Then, find what order in its group. That order is the embedded value. The information can be extracted from each group till all the pixels are extracted. From the experimental results, the method has the good embedding capacity and the image quality. Additionally, the proposed method will not be affected by the change of the order of the color palette after embedded since we keep the highest frequency for each cluster.