ABSTRACT

Abstract-The recently created technology of steganography entices a wide audience from the casual observer, to the scientific professional. Steganography is defined as the art and science of writing hidden messages in such a way that the hidden message is unnoticed by someone that is not aware of its content. This paper attempts to reveal new and current angles of steganography. When the hidden message is an image which is encoded into an audio file, the process is termed as Sound Steganography. In this work, we have designed a practically secure sound steganographic method, an algorithm which could encode a picture into sound and then read it again in order to obtain image through sound. The algorithm used is simple and optimal, named the color palette substitution. Sound steganography is implemented in two stages, namely image cryptography, where the image is encoded to sound, being the first and reading the sound in a frequency spectrum, being the second. Also the image converted audio is embedded over another music file to form a stronger encryption. MATLAB 7.0.1 with image processing and signal processing toolboxes is used as the development tool for implementing the algorithm.

Abstract-Now a days, the digital world is most focused on storage space and speed. With the growing demand for better bandwidth utilization, efficient image data compression techniques have emerged as an important factor for image data transmission and storage. To date, different approaches to image compression have been developed like the classical predictive coding, popular transform coding and vector quantization. Several second generation coding schemes or the segmentation based schemes are also gaining popularity. Practically efficient compression systems based on hybrid coding which combines the advantages of different traditional methods of image coding have also being developed over the years. In this paper, different hybrid approaches to image compression are discussed. Hybrid coding of images, in this context, deals with combining two or more traditional approaches to enhance the individual methods and achieve better quality reconstructed images with higher compression ratio. Literature on hybrid techniques of image coding over the past years is also reviewed. An attempt is made to highlight the neuro-wavelet approach for enhancing coding efficiency.

Aims: To introduce a cost-effective tool for reading and interpreting machine printed text in document images and save as computer-processable codes. Study Design:  In this work, emphasize is given on extracting uppercase & lowercase letters and numerals from document images by the technique of segmentation and feature extraction using MATLAB Image Processing toolbox. Place and Duration of Study: Department of Engineering, Ibri College of Technology, between September 2017 and May 2018. Methodology: Necessary information about existing algorithms on character recognition is collected by review of relevant literature available in journals, books, manuals and related documents. Suitable architecture and novel algorithm for a simple, low cost, low complexity, highly accurate system is developed as per the specifications and reviewed literature. Functionality of the design is verified using simulation software MATLAB. Results: The proposed method can extract characters from document image (which may be scanned or camera captured) of any font size, colour, space and can be rewritten in an editable window like Notepad, WordPad where the characters can even be edited; thus, improving accuracy and hence, saves time. Conclusion: This algorithm gives promising results that have been obtained on a number of images in which almost all characters are retrieved. It also gives 90 percent accuracy for all printed characters.