8 research outputs found

    Seismic Data Compression using Wave Atom Transform

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    Seismic data compression SDC is crucially confronted in the oil Industry with large data volumes and Incomplete data measurements In this research we present a comprehensive method of exploiting wave packets to perform seismic data compression Wave atoms are the modern addition to the collection of mathematical transforms for harmonic computational analysis Wave atoms are variant of 2D wavelet packets that keep an isotropic aspect ratio Wave atoms have a spiky frequency localization that cannot be attained using a filter bank based on wavelet packets and offer a significantly sparser expansion for oscillatory functions than wavelets curvelets and Gabor atom

    Digital Color Image Watermarking using DWT-DCT Coefficients in RGB Planes

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    Digital image watermarking is used to identify the authenticity and integrity and to show the identity of its owners. This paper presents a more secure method for copy right protection. In the proposed method, the color image is decomposed into 3 color channels Red, Green and Blue and then DWT and DCT are applied to B channel of the R, G and B channels. The colored Watermark image is decomposed into R, G, B channels and DCT is applied to all the channels separately. R, G, B channels of watermark image are embedded into mid frequency coefficients of B channel already selected. The performance of proposed algorithm is measured by using Mean Square Error, Peak Signal to Noise Ratio, Standardized Correlation and Normalized Correlation. A comparative study of proposed scheme with the existing methods which uses DWT-DCT transforms is carried here and results shown

    Robust Watermarking Method for Color Images using DCT Coefficients of Watermark

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    Digital technologies are playing a vital role in the present communication system. This paper presents a robust and secure watermarking method to protect the copyright information of multimedia objects. In the proposed method, Discrete Wavelet Transform and Discrete Cosine Transform are applied on the cover image and then Discrete Cosine Transform coefficients of watermark image are embedded into transformed cover image. The experimental result shows the performance evaluation of the proposed method by the quality metrics as PSNR for watermarked image and NC for extracted watermark image and we have compared the results with the existing transformation methods in frequency domain based on attacks

    Character Segmentation for Telugu Image Document using Multiple Histogram Projections

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    TEXT line segmentation is one of the major component of document image analysis. Text line segmentation is necessary to detect all text regions in the document image. In this paper we propose an algorithm based on multiple histogram projections using morphological operators to extract features of the image. Horizontal projection is performed on the text image, and then line segments are identified by the peaks in the horizontal projection. Threshold is applied to divide the text image into segments. False lines are eliminated using another threshold. Vertical histogram projections are used for the line segments and decomposed into words using threshold and further decomposed to characters. This approach provides best performance based on the experimental results such as Detection rate DR (98%) and Recognition Accuracy RA (98%)

    A New Method for Gray Level Image Thresholding Using Spatial Correlation Features and Ultrafuzzy Measure

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    One of the most recent techniques employed to estimate an optimal threshold of a gray level image for segmentation is ultrafuzzy measures. In this paper, we introduce relative fuzzy membership degree (RFMD) taking spatial correlation among the pixels in the image into account. We also propose a novel thresholding technique by combining two-dimensional histogram, which was determined by using the gray value of the pixels and the local average gray value of the pixels using ultrafuzziness and RFMD. Compared to fuzzy membership degree, RFMD of type-II fuzzy sets and ultrafuzzy measure is able to better segment critical gray level images. It was observed that the outcome is so encouraging in objective and subjective perspectives over the existing method for all varieties of images
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