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Main goal of steganography is to communicate securely in a completely undetectable manner. It is an art of hiding secret data in an innocently looking dummy container. In the Steganographic process, communication is masked to make the hidden message not discernible to the observer. Hidden message may be textual or image. In this paper, a novel image(More)
In this paper, a novel method developed for classification of arecanuts based on texture features. A Gabor response co-occurrence matrix (GRCM) is constructed analogous to Gray Level co-occurrence matrix (GLCM). Classification is done using kNN and Decision Tree (DT) classifier based on GRCM features. There are twelve Gabor filters are designed (Four(More)
In this paper we propose a novel statistical face recognition method that uses a new multiresolution analysis called Shearlet transform for facial texture features representation. In recent years Shearlet transform has emerged as the most successful framework for the efficient representation of multidimensional data in which directional information is(More)
  • Suresha M, Ajit Danti, +4 authors Anil K. Jain
  • 2014
In the proposed work, classification of diseased and undiseased arecanut have been determined using texture features of Local Binary Pattern (LBP), Haar Wavelets, GLCM and Gabor. This work has been carried out in two stages. In the first stage, LBP have been applied on each color component of HSI and YCbCr color models and histogram of LBP is generated. The(More)
— The Local Binary Pattern (LBP) operator is a powerful means of micro texture description that has been used in texture analysis of arecanut in this work. The Gabor filters and GLCM (Gray Level Co occurrence Matrix) will capture data with different scale and angle. The Gabor and GLCM based LBP has been used for classification of arecanut data. In the(More)
Image Steganography using Discrete Wavelet Transform(DWT) and Hybrid Wavelet Transform, the secret image is first compressed using hybrid wavelet transform and then encrypted and embedded in frequency domain. The network bandwidth can be saved by compressing the secrete image with out compromising in the quality of the secret image. The cover and secret(More)