Steganography is the technique that hides any data behind other data. Many different carrier file formats can be used but digital images are the most popular ones because of their frequency on the Internet. Steganography are of four typestext, image, audio and video. There are many Steganography techniques for hiding secret information in images. A survey of image steganography is done here and all the techniques to hide a secret image behind an cover image are described.

In this paper, online handwritten Devnagari word recognition system is proposed and discussed. The increase in usage of handheld devices which accept handwritten data as input created a demand for application which analyze and recognize data efficiently. Due to the popularity of digital device, we use Smartphone as input device. Input image is drawn on Smartphone. Feature extraction of input image is done by android technology. Using that features HMM recognizes the word. Experimental results show advantages of this method in the field of handwriting recognition.

Image inpainting is the process of restoring missing pixels in digital images in a plausible way. A study on image inpainting technique has acquired a significant consideration in various regions, i.e. restoring the damaged and old documents, elimination of unwanted objects, cinematography, retouch applications, etc. Even though, limitations exist in the recovery process due to the establishment of certain artifacts in the restored image areas. To rectify these issues, more and more techniques have been established by different authors. This survey makes a critical analysis of diverse techniques regarding various image inpainting schemes. This paper goes under (i) Analyzing various image inpainting techniques that are contributed in different papers; (ii) Makes the comprehensive study regarding the performance measures and the corresponding maximum achievements in each contribution; (iii) Analytical review concerning the chronological review and various tools exploited in each of the reviewed works. Finally, the survey extends with the determination of various research issues and gaps that might be useful for the researchers to promote improved future works on image inpainting schemes.

Many face recognition algorithms have been proposed that help faces to be identified on systems. The aim of the paper is to compare the performance of transform domain techniques and Vector Quantization techniques. The system considers the full and partial feature vector sizes of images. In addition to this, the proposed system tries to improvise by extracting the face region before feature extraction is done. The system recognizes the face region using YCbCr color space to reduce the effect of lightening positions and intensities. General TermsSecurity, Biometric system.

Face Recognition is a computer application that is drawing much attention in the computer society in the areas like network security, privacy, video conferencing and content indexing and retrieval. These systems should be able to correctly detect and recognize different faces from the images. Many face recognition algorithms have been proposed that help faces to be identified on systems. The aim of the proposed system is to improvise by extracting the face region before feature extraction is done. Any image will be subjected to different lightening positions and intensities. Hence the system recognizes the face region using YCbCr color space. This paper also compares the results of different transform domain techniques applied further in the process.