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Jain, Yogendra Kumar
- AODV-TP and Wormhole Attack Detection in MANET
Authors
1 Samrat Ashok Technological Institute Vidisha (M. P.) 464001, IN
Source
Networking and Communication Engineering, Vol 2, No 8 (2010), Pagination: 248-255Abstract
With the evolution of computer networks extending boundaries, Mobile Ad hoc Network (MANET) has emerged as a new leading edge of technology to provide any where, any time communication. Unlike wired network, the mobile ad hoc network does not need any infrastructure, so it is very difficult to perform any kind of centralized anagement and control. The routing in Mobile adhoc network is difficult and number of reactive routing protocols like AODV, DSR, and DSDV has been implemented. In the first part of this work, we propose a new algorithm AODV-TP to improve existing on demand routing protocol and an attempt has been made to compare the performance of proposed algorithm (AODV-TP) with existing algorithm DSR and AODV. Ad hoc networks are susceptible to number of attacks, due to precise physical protection of each node and changeable nature of connection security in mobile ad hoc is distinctly difficult to achieve. This paper introduces the wormhole attack, a severe attack in ad hoc network that is very stimulating to defend against. This paper proposes an easiest way to detect wormhole attacks using RBM technique. The presented method shows that solution can be implemented using reactive protocol called AODV-TP.
Keywords
Mobile Ad Hoc Network, AODV, DSR, Wormhole Attack, DSDV.
- Image Sharpness and Contrast Enhancement with Noise Reduction using Logarithmic Image Processing Model with Modified Decision based Unsymmetric Trimmed Median Filter
Authors
1 Department of CSE, Samrat Ashok Technological Institute, Vidisha (M.P.), IN
Source
Digital Image Processing, Vol 4, No 16 (2012), Pagination: 902-909Abstract
Image enhancement is basic problem in the field of image processing & it can be subdivided into many categories like edge enhancement, smoothing, contrast enhancement, bright enhancement, sharpness enhancement etc. The classical approach treats the operations using linear systems which creates many computational problems and also does not match to human visual perception and interpretation logic. In this work we propose a LIP (Logarithmic Image Processing) technique in combination with MDBUTMF (Modified Decision Based Unsymmetric Trimmed Median Filter) for contrast and sharpness enhancement with capability to suppress the noise. LIP uses non-linear operations for image manipulation which are computationally effective. In LIP, image processing specific arithmetic operations are introduced which ensure that there is no loss of information in the form of ―out-of-range‖ pixel values. MDBUTMF is a very efficient median filter and it is capable of de-noising images which are corrupted with high density salt and pepper noise. Thus the combination of these techniques results in an efficient image enhancement algorithm. MDBUTMF is first applied to de-noise the input image. The de-noised image is further processed by LIP based enhancement methods to generate the final output. All the implementation work has been done in MATLAB 10.0 image processing tool box. Simulation results show a marked improvement in performance in terms of removal of noise, contrast, sharpness, detail enhancement, and Overall quality of image as compared to existing algorithms.Keywords
Image Enhancement, Sharpness Enhancement, Noise Reduction, LIP (Logarithmic Image Processing), Median Filter.- Adaptive approach for Image Fusion using Curvelet Transform and Genetic Algorithm
Authors
1 Department of Computer Science & Engineering at Samrat Ashok Technological Institute, Vidisha, M.P., IN
2 Department of Computer Science & Engineering at Samrat Ashok Technological Institute, Vidisha, M.P, IN
Source
Digital Image Processing, Vol 4, No 15 (2012), Pagination: 850-857Abstract
Although image fusion is a technique of merging two or more images that have consilient information to form a fused image which contains more accurate information of the image than any of the individual source images. In this paper, we proposed a multi-view and multi-modal Fusion, and Pixel level fusion approach. At first stage we perform feature extraction of image which plays a major role in the implementation of fusion approaches. Prior to the merging of images, salient features, present in all source images, are extracted using an appropriate feature extraction procedure. For the same we use transform domain texture feature Extraction (Curvelet) for better edge representation. After that fusion is performed on these extracted features vector by using genetic algorithm to get the more optimized combined image. Performance evaluation has been carried out of using the RMSE, PSNR and IQI. The results of the proposed method is compared with the existing techniques of image fusion using DWT. Experimental results shows that of curvelet transform and GA is better than DWT fusion method.
Keywords
Curvelet, Discrete Wavelet Transform, Feature Vectors, Genetic Algorithm, Image Fusion, Texture Feature Extraction.- Performance Analysis and Comparison of Image Compression Using DCT and Wavelets
Authors
1 Computer Science & Engineering, Samrat Ashok Technological Institute, Vidisha-464001 (M.P.), IN
2 Computer Science & Engineering, Laxminarayana College of Engineering, Bhopal (M.P.), IN
Source
Digital Image Processing, Vol 2, No 5 (2010), Pagination: 147-156Abstract
To overcome the limitations of the bandwidth and storage, the images must be effectively compressed for efficient utilization of available resources such as storage and bandwidth of communication media. The objective of this paper is to provide the performance analysis and comparison of image compression using Discrete Cosine Transform (DCT) and Wavelet Transform (WT). The performance analysis and comparison is carried out on equal footing. The choice of transform used depends on a number of factors, in particular, computational complexity and coding gain. In present scenario, the most effective and popular way to achieve efficient compression of images are based on either Discrete Cosine Transform (DCT) or Wavelet Transform (WT). The paper discusses important features of both the discrete cosine transform (DCT) and the wavelet transform (WT) in compression of still images. DCT represent an image as a superposition of cosine functions with different discrete frequencies i.e. the basis of Discrete Cosine Transform (DCT) is cosine functions, while the basis of Wavelet Transform (WT) is wavelet function that satisfies requirement of multi-resolution analysis. The influences of image contents of variety of images at different compression ratios are assessed. The test images selected for experiment are of different frequency content, size and resolution. Two quality measures are used: Peak Signal to Noise Ratio (PSNR) and visual quality of image. In this paper, we have analyzed visual quality of image at a compression ratio of 50:1 using both DCT and WT (at decomposition level 5) for image compression on the variety of test images. Our analysis reveals that for images, the wavelet transform outperforms the DCT in both peak signal-to-noise-ratios as well as in visual quality of image.Keywords
Discrete Cosine Transform, Wavelet Transform, PSNR, Image Compression, Compression Ratio, Image Quality.- Hand Gesture and Speech Giving New Dimensions in Design of Intelligent Machine Using Kalman Fusion
Authors
1 Deptt of EC Engg., Akshaya Institute of Technology–Tumkur (Karnataka), IN
2 Deptt. of CS Engg., Samrat Ashok Technological Institute – Vidisha (M.P.), IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 6, No 8 (2014), Pagination: 301-305Abstract
Developing Intelligent Machines is old concept but new era of advancement. Different researches are being carried out and many achievements has also been achieved to design smart machine having brain. The aim of this paper is to discuss and analyze two main challenges in this field, First is discussion based on human way of communication Hand Gesture and Speech can be the best combination to design user-friendly machine as they are co-expressive to each other and capable of giving complete meaning to any command. Second, comparing various level of fusion of heterogeneous inputs and discussing the steps and advantage of Kalman fusion in detail. This paper will help in will be helpful in improving the efficiency in Human Machine Interaction using Multimodalities.
Keywords
Feature Level Fusion, Hand Gesture, Intelligent Machine Kalman Fusion, Speech.- Motion Estimation and Tracking of Hand Using Harris-Laplace Feature Based Approach
Authors
1 Department of Electronics and Communication, SATI, Vidisha, M.P, IN
2 Department of Computer Science and Engineering, Samrat Ashok Technological Institute (Engineering College), Vidisha, M. P., IN
Source
Biometrics and Bioinformatics, Vol 9, No 8 (2017), Pagination: 157-163Abstract
Hand is now being accepted as most promising, natural and simple modality in real time applications. There are many natural factors, like shape and speed and environmental factor, like view-point, scale etc. which effect deeply in efficiency of Dynamic Hand Gesture Recognition System. The current–state of art is still faces many challenges in finding efficient tracking mechanism. This paper aims to present a novel approach of using Harris- Laplace to visually locate and track hand in each frame. The paper emphasizes that detection of ‘corners’ as interest points show high performance and less computation, in case of Hand recognition. The results are also compared with other local features like, SIFT and SURF techniques and found that in case of dynamic hand tracking ‘Harris –Laplace’ detection shows better performance.
Keywords
Dynamic Hand Gesture Recognition, Feature Descriptors, SIFT, SURF, Harris-Laplace.References
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