Tanuja Sarode

Image hashing using AQ-CSLBP with double bit quantization

This paper presents a novel image hashing method for authentication and tampering detection. Creation, modification and transfer of multimedia data becomes an easy task due to digitization. Integrity is very important for crucial and sensitive matters like medical records, legal matters, scientific research, forensic investigations and government documents. Image hashing is one of the popular method to maintain integrity of image. We proposed AQ-CSLBP (Average Compressed Center Symmetric Local Binary Pattern) as a feature descriptor for image hashing. First, image is divided into sub blocks, AQ-CSLBP is applied on each sub block to generate 8 bin histogram as a feature. Then, we used double bit quantization to generate hash code for the image. The proposed method is compared with the existing methods by way of quantitative analysis, it has been proved that the proposed method works well in authentication scenario with less hash length and more discrimination power.

Image hashing by SDQ-CSLBP

Approach for image hashing is to use powerful feature descriptor which captures essence of an image. Applications of image hashing lies in the area of content authentication, structural tampering detection, retrieval and recognition. Hashing is a compact summarized information of an image. Center Symmetric Local Binary Pattern (CSLBP) is one of the powerful texture feature descriptor which captures the smallest amount of change. Using CSLBP, appressed hash code can be obtained for an image. If CSLBP feature is weighted by a boost factor, it will enhance success rate of an image hashing. The proposed method of SDQ-CSLBP extract texture feature using CSLBP with standard deviation as weight factor. Standard deviation which represents local contrast is also a powerful descriptor. Resultant histogram of CSLBP is of 16 bin for each block of an image. Further it can be compressed to 8 bin by using the flipped difference concept. Without a weight factor, compressed CSLBP has low discrimination power. Experimental results show that the proposed method is robust against content preserving manipulation and sensitive to content changing and structural tampering.

Digital image encryption using improved chaotic map lattice

Chaotic map lattice (CML) has been used recently for digital image encryption; however, it has several flaws in terms of irreversibility and violates some basic principles of cryptography. In this work, we propose an improved CML (ICML) using piecewise linear chaotic maps instead of logistic map to achieve better chaotic properties, and zigzag coupling direction for chained iteration in ICML. The results of several experimental, statistical analysis and key sensitivity tests show that the proposed image encryption scheme provides an efficient and secure way for image encryption, and has properties desirable in a good security cryptosystem.

Biometric watermarking using partial DCT-Walsh wavelet and SVD

Biometric has ever increasing demand in the field of security. However, integrity and security of biometric used to authenticate a legal user are the inherited problems of it. Since watermarking hides one form of digital data into other, its use in securing biometric data gives an added advantage. This concept has led to biometric watermarking technique in which one biometric can be embedded into another biometric feature of user to enhance security. In this paper a robust biometric watermarking technique using face images as host and iris images as watermark has been proposed with the combination of hybrid wavelet and Singular Value Decomposition. DCT-Walsh hybrid wavelet transform is used in its partial form (column transform) on host and watermark images. Low frequency coefficients of partially transformed hosts are subjected to SVD. Singular values of partially transformed watermark are adaptively scaled and are embedded in these singular values of host. Robustness of proposed technique is evaluated against compression, selective and random cropping, noise addition and resizing attack. Average absolute pixel difference between embedded and extracted watermark is used as similarity measure between them. Proposed technique is observed to be highly robust against these attacks except selective cropping. However this limitation is eliminated when iris images are embedded in middle frequency coefficients of host.

Halftone Image Data Compression Using Kekre’s Fast Code Book Generation (KFCG) Algorithm for Vector Quantization

Halftone technique is well known for printing where binary data is required. 8:1 compression ratio is achieved by half toning method. To get higher compression ratio the same technique can be used in image processing. In our earlier work different half toning operators are proposed. The half toning operator of size 3X3 which effectively take only one tap operation. Hence the computational complexity and memory space is reduced. For further compression of the image data Vector Quantization technique is used. Vector Quantization technique itself gives very high compression ratio. To avoid time and computational complexity Kekre’s Fast Code Book Generation (KFCG) algorithm is used. In this paper we have used 8, 16, 32, 64, 128 and 256 codebook sizes are used. The pixel group of 2X2 size is used. The experimental results are obtained for various images. For image data compression and image quality measurement, we have used Compression Ratio and Mean Square Error as measuring parameters respectively. We have got result with good Compression Ratio and acceptable image quality. This proposed combination of two compression technique is suitable for video data streaming, where low bit rate for data transmission is the major constraint.

Adaptive filtering a descreening approach for color scanned halftones

To print ceaseless tone images, Electrophotographic printers mostly use halftoning method. Scanned pictures procured from such hard transcripts are generally wrecked by screen like antiquities. Recently an approach for reviving relentless image from scanned halftone picture was accomplished. This new model considers both printing deformities and halftone motifs. At first denoising computation is proposed to evacuate printing noise and then, Screen Frequency of scanned halftone picture is estimated and Local Gradients are calculated. Next, Gaussian Filter whose variable are dynamically adapted is exerted to compute basic persistent tone value of each pixel and diminish twists. At the end, Edge- Sharpening technique is propounded to shield edges of checked picture. Finally descreened Scanned images with unremitting tones are acquired. In this paper this technique is extended for color scanned halftone images. Demonstrations show that the proposed method can recuperate perpetual tone pictures from the real scanned facsimile.

Chaotic Truncated Sine Series with MOD operator for Image Encryption

With the Advancement in technology, transmission of information has become an easy process. This transmission will lead to attacks if the information is not secured in some form. One of the methods involve encrypting the information, be it a digital image. In this paper, a novel chaotic map is introduced which is based on truncated Sine series. As there is no limit on the Sine series, for experimental purpose three truncated sine series are used. Experimental results prove its chaotic nature and usage in encrypting images. It also proves maximum four terms are enough to give close results as obtained by Sine Map.

Performance superiority of hybrid DKT-DCT wavelet compared to DKT, DCT individual transforms and their wavelets in image compression

This paper proposes simple and novel image compression method using transforms. Discrete cosine Transform (DCT) and Discrete Kekre Transform (DKT) are applied on image individually. Wavelet transform of DCT and DKT is generated using Kekres algorithm of wavelet generation. Wavelet transform gives better energy compaction than individual transform. It is reflected in reconstructed image quality of wavelet transforms. Further hybridization of two transform is used and hybrid wavelet transform using DKT and DCT is generated and applied on images. It combines properties of both, Kekre transform and DCT. Hybrid wavelet transform gives lesser error than wavelet transform and individual orthogonal transform.

Kekre’s fast codebook generation in VQ with various color spaces for colorization of grayscale images

Colorization is the term which means to color any gray scale image. In digital image processing terms colorization of grayscale image is nothing but assigning the red, green and blue color component values to each gray value of grayscale image [1, 2]. Colorization is very difficult because it involves assigning three-dimensional (RGB) pixel values to an image which varies along only one dimension (luminance or intensity) [3]. Since different colors may have the same luminance value but vary in hue or saturation, the problem of colorizing grayscale images has no inherently ‛unique’ solution [4]. So user intervention becomes trivial in colorization process to select the ‛better’ match (red, green and blue values) for every grayscale pixel. In [1, 2] authors have proposed some of the simple approaches for colorization of grayscale images, where user intervention is needed only to select the source color image to be used to generate color palette. In [1, 5] different color spaces and pixel window sizes are worked out for coloring grayscale images. All these techniques gives the results subjective to the source color image considered for coloring are very heavy with respect to time complexity. To speed up the process different search algorithms are proposed in [1, 4]. But everywhere the size of source color image is assumed to be equal to or more than to be colored target grayscale image. The paper presents novel colorization technique where this size dependency of source color image and target grayscale image are taken out. The proposed technique generates color palette using vector quantization codebook generation approach. Here Kekre’s fast codebook generation (KFCG) [16, 20, 21] algorithm is used.

Image hashing by CCQ-CSLBP

Recent trends and also statistics show that the hashing concept has been gaining importance because its application lies in the area of authentication, retrieval and recognition. The proposed hashing method CCQ-CSLBP (Compressed CSLBP with Correlation Coefficient) for authentication utilized correlation coefficient as a weight factor in CSLBP. CSLBP is a texture operator, whose performance is better than LBP, in terms of rotation invariance, differentiation power and less number of histogram bin. In CSLBP, histogram of each sub block is represented by 16 bin. Reduction in number of histogram bin is achieved by the flipped difference concept. Proposed method takes the advantage of correlation coefficient as a boosting factor during histogram construction, to increase the discrimination power of compressed CSLBP. With the use of correlation coefficient, results of CSLBP improved, in terms TPR and FPR. CCQ-CSLBP is evaluated, based on normalized hamming distance and ROC characteristics.