ICTACT Journal on Image and Video Processing

C. Morris ¹, R. S. Rajesh ¹

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN

Abstract

The objective of Image fusion is to combine the information from number of images of the same scene from different sensors or the images with focus on different objects. The result of image fusion is an image which is more informative and of better quality. In this paper a detailed survey of Select Maximum /Minimum and principal component analysis for spatial domain image fusion techniques is done. On the basis of the survey an improved spatial domain fusion technique is proposed. The proposed spatial domain technique output performs as the state of the art spatial domain techniques.

Keywords

Spatial Domain, Simple Maximum/Minimum, PCA.

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D. Kesavaraja ¹, R. Balasubramanian ², R. S. Rajesh ², D. Sasireka ³

Affiliations
1 Department of Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tamil Nadu, IN
3 Department of Information Technology, Jayamatha Engineering College, Tamil Nadu, IN

Abstract

This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

Keywords

Parallel Algorithms, Region Growing, Image Enhancement, Image Segmentation, Parallel Performance.

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K. Jaya Priya ¹, R. S. Rajesh ²

Affiliations
1 Mother Teresa Women’s University, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tamil Nadu, IN

Abstract

In this paper, we propose novel face recognition method based on local appearance feature extraction using hybrid mode of local ridge-let and fused dual-tree complex wavelet transform (DT-CWT). It provides a local multiscale description of images with good directional selectivity, effective edge representation and invariance to shifts and in-plane rotations. In the dual-tree implementation, two parallel dis-crete wavelet transform (DWT) with different lowpass and highpass filters in different scales are used. The linear combination of sub-bands generated by two parallel DWT is used to generate 6 different directional subbands with complex coefficients. It is insensitive to illumination variations and facial expression changes. 2-D dual-tree complex wavelet transform is less redundant and computationally efficient. The fusion of local DT-CWT coefficients of detail subbands and local Finite Ridgelet Transform (FRIT) coefficients of approxi-mate subbands of DT-CWT are used to extract the facial features which improve the face recognition with small sample size in less computation. The local features based methods have been success-fully applied to face recognition and achieved state-of-the-art per-formance. Normally most of the local appearance based methods the facial features are extracted from several local regions and concate-nated into an enhanced feature vector as a face descriptor. In this approach we divide the face into several (m×m) non-overlapped paral-lelogram blocks instead of square or rectangle blocks. The local mean and standard deviation of hybrid FRIT and fused DT-CWT coeffi-cients are used to describe the face image. Experiments, on two well-known databases, namely, Yale and ORL databases, shows the Local hybrid FRIT and fused DT-CWT approach performs well on illumi-nation, expression and perspective variant faces with single sample compared to PCA and global DT-CWT. Furthermore, in addition to the consistent and promising classification performances, our pro-posed Hybrid Local FRIT and fused DT-CWT based method has a really low computational complexity.

Keywords

Gabor Wavelet Transform, Finite Ridgelet Transform, Dual Tree Discrete Wavelet Transform, Dual Tree Complex Wavelet Transform, PCA, Parallelogram Regions.

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Dejey ¹, R. S. Rajesh ¹

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN

Abstract

In this paper, two approaches for color image watermarking in the wavelet domain are proposed. The first approach utilizes only the chrominance content of the color image for watermarking after performing a single level DWT (Discrete Wavelet Transform) decomposition and hence named as DWTC whereas the second approach utilizes both the luminance and chrominance content for watermarking and hence termed as DWTLC. Watermark which is a logo is scrambled before embedding to increase its robustness. Watermarking is done on the approximation band coefficients chosen randomly by a function in Lab space. Both the proposed approaches result in watermarked images of high quality. The robustness of both the approaches is verified by the conduct of various attacks on the watermarked images and is compared with an existing SCDFT based approach and a DWT based approach. Experimental results show that DWTC is robust to non geometric attacks like filtering, blurring, sharpening, histogram equalization, JPEG compression and to geometric attacks like additive noise and scaling. DWTLC watermarking also shows robustness to all the above attacks. Further, both the approaches resist collusion attack even with a minimum number of colluders and with increasing number of colluders there is much distortion in the visual quality of the colluded images.

Keywords

DWT, Luminance, Chrominance, Attacks, Collusion.

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