Visual cryptography is considered to be a vital technique for hiding visual data from intruders. Because of its importance, it finds applications in various sectors such as E-voting system, financial documents and copyright protections etc. A number of methods have been proposed in past for encrypting color images such as color decomposition, contrast manipulation, polynomial method, using the difference in color intensity values in a color image etc. The major flaws with most of the earlier proposed methods is the complexity encountered during the implementation of the methods on a wide scale basis, the problem of random pixilation and insertion of noise in encrypted images. This paper presents a simple and highly resistant algorithm for visual cryptography to be performed on color images. The main advantage of the proposed cryptographic algorithm is the robustness and low computational cost with structure simplicity. The proposed algorithm outperformed the conventional methods when tested over sample images proven using key analysis, SSIM and histogram analysis tests. In addition, the proposed method overshadows the standard method in terms of the signal to noise ratio obtained for the encrypted image, which is much better than the SNR value obtained using the standard method. The paper also makes a worst case analysis for the SNR values for both the methods.

The paper develops an efficient people surveillance system capable of tracking multiple people on different terrains. Recorded video on rough terrains is affected by jitters resulting into significant error between the desired and captured video flow. Video stabilization is achieved by calculating the motion and compensational parameters using the LSE analytical solution to minimize the error between present and desired output video captured from an autonomous robot’s camera moving on a rough terrain used for surveillance of unidentified people. This is the first paper to the best of our knowledge which makes use of this method to design mobile wireless robot for human surveillance applications. As the method used is fast then conventional methods, making the proposed system a highly efficient surveillance system as compared to previous systems. The superiority of the method used is demonstrated using different evaluation parameters like RMCD, variability and reliability. The system can be used for surveillance of people under different environmental conditions.