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In this paper, we propose a reversible data hiding method in the spatial domain for compressed grayscale images. The proposed method embeds secret bits into a compressed thumbnail of the original image by using a novel interpolation method and the Neighbour Mean Interpolation (NMI 1.INTRODUCTIONSecret information exchange is a vital requirement of persons and institutions in society. Channelling secret information over public networks has proven to be very insecure. There is a great need for protective methods for sending secret information.Cryptography is traditionally the first method implemented for protection. Cryptography however, has a few drawbacks. Encrypted data can be easily identified during transmission hence attracting unwanted attention to the packaged information. With increased computing power the possibility of cracking the cryptographic technique increases. Information hiding is an alternative strategy that can be used to protect sensitive secret information. While cryptography protects the content of messages data hiding conceals the existence of secret information.In general, information hiding (also called data hiding or data embedding) includes digital watermarking and steganography [1].Data hiding technology prevents information from being detected, stolen or damaged by unauthorized users during transmission. The word stegano-graphy is a Greek word meaning "covered writing" the art of hiding secret information in ways that prevent detection [2]. The traditional method of encryption [3] can still be applied to the message and then a stegonographic approach used to ensure undetected delivery.Information can be hidden in many ways. Hiding information may involve straight message insertion whereby every bit of information in the cover is encoded or it may selectively embed messages in noisy areas that draw less attention. Messages may also be dispersed in a random fashion throughout the cover data.

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This paper describes a radial layout method for displaying B + -tree data structures. We present an algorithmic framework for computing the node positions that result in a planar drawing. Layout issues related to displaying the internal structure of the nodes are addressed. Each field value and associated pointer that comprises the internal structure of the node is considered a subnode. The drawing technique uses different polygonal shapes for the subnodes that allow curvature to the design. We discuss the layout of text labels for the fields of the nodes which provides good readability and which preserves the semantics of the data structure. The edge positioning shows the association of the pointers with their corresponding field label. The radial drawing of the B + -tree makes better use of the display space than the traditional hierarchical drawing.