Image Segmentation Based on Doubly Truncated Generalized Laplace Mixture Model and K Means Clustering

The present paper aims at performance evaluation of Doubly Truncated Generalized Laplace Mixture Model and K-Means clustering (DTGLMM-K) for image analysis concerned to various practical applications like security, surveillance, medical diagnostics and other areas. Among the many algorithms designed and developed for image segmentation the dominance of Gaussian Mixture Model (GMM) has been predominant which has the major drawback of suiting to a particular kind of data. Therefore the present work aims at development of DTGLMM-K algorithm which can be suitable for wide variety of applications and data. Performance evaluation of the developed algorithm has been donethrough various measures like Probabilistic Rand index (PRI), Global Consistency Error (GCE) and Variation of Information (VOI). During the current work case studies forvarious different images having pixel intensities has been carried out and the obtained results indicate the superiority of the developed algorithm for improved image segmentation

Tool and work piece vibrations measurement - a review

Tool condition monitoring is one of the important aspects in machining process to improve tool life. It comprises three important steps namely machining data acquisition, data analysis and decision making. Vibration in metal cutting has direct impact on the tool life as well as surface roughness. The present study focused on measurement of vibration during the machining process. Data acquisition is made by using various types of sensors. A wide variety of technologies like contact and non contact sensors have been used for real time data acquisition of tool or work piece vibrations. Research works carried out by many authors is highlighted in measurement of cutting tool and machine tool vibrations using different sensors. Influence of various input parameters like tool geometry, feed, speed and depth of cut on the magnitude of vibrations is discussed. Influence of vibration on surface roughness, tool life and power consumption is reviewed. Three dimensional vibration measurement with single Laser Doppler Vibrometer is also covered for precise analysis of vibration

Localization of Copy-Move Forgery in speech signals through watermarking using DCT-QIM

Digital speech copyright protection and forgery identification are the prevalent issues in our advancing digital world. In speech forgery, voiced part of the speech signal is copied and pasted to a specific location which alters the meaning of the speech signal. Watermarking can be used to safe guard the copyrights of the owner. To detect copy-move forgeries a transform domain watermarking method is proposed. In the proposed method, watermarking is achieved through Discrete Cosine Transform (DCT) and Quantization Index Modulation (QIM) rule. Hash bits are also inserted in watermarked voice segments to detect Copy-Move Forgery (CMF) in speech signals. Proposed method is evaluated on two databases and achieved good imperceptibility. It exhibits robustness in detecting the watermark and forgeries against signal processing attacks such as resample, low-pass filtering, jittering, compression and cropping. The proposed work contributes for forensics analysis in speech signals. This proposed work also compared with the some of the state-of-art methods

Localization of Copy-Move Forgery in speech signals through watermarking using DCT-QIM

Digital speech copyright protection and forgery identification are the prevalent issues in our advancing digital world. In speech forgery, voiced part of the speech signal is copied and pasted to a specific location which alters the meaning of the speech signal. Watermarking can be used to safe guard the copyrights of the owner. To detect copy-move forgeries a transform domain watermarking method is proposed. In the proposed method, watermarking is achieved through Discrete Cosine Transform (DCT) and Quantization Index Modulation (QIM) rule. Hash bits are also inserted in watermarked voice segments to detect Copy-Move Forgery (CMF) in speech signals. Proposed method is evaluated on two databases and achieved good imperceptibility. It exhibits robustness in detecting the watermark and forgeries against signal processing attacks such as resample, low-pass filtering, jittering, compression and cropping. The proposed work contributes for forensics analysis in speech signals. This proposed work also compared with the some of the state-of-art methods

A Multi-Objective Fuzzy Evolutionary Algorithm for Job Scheduling on Computational Grids

Scheduling jobs in grid computing is a challenging task. The job scheduling is a process of optimization of resource allocation for job completion in a optimum amount of time. There are various solutions like using dynamic programming, evolutionary algorithms etc., in literature. However, till date, no algorithm is found to be the best. This paper attempts a new job shop scheduling problem using a recent JAYA optimization algorithm. This work proposes a fuzzy based JAYA algorithm to minimize the makespan of the selected job scheduling problem. The main feature proposed is its simplicity due to the simple JAYA algorithm compared to other existing evolutionary algorithms. Experiments are conducted on four different data sets and the results are compared with other evolutionary and fuzzy based evolutionary algorithms. The proposed fuzzy based JAYA produced compatible results in terms of average makespan, flowtime and fitness

A Hybrid Digital Watermarking Approach Using Wavelets and LSB

The present paper proposed a novel approach called Wavelet based Least Significant Bit Watermarking (WLSBWM) for high authentication, security and copyright protection. Alphabet Pattern (AP) approach is used to generate shuffled image in the first stage and Pell’s Cat Map (PCM) is used for providing more security and strong protection from attacks. PCM applied on each 5×5 sub images. A wavelet concept is used to reduce the dimensionality of the image until it equals to the size of the watermark image. Discrete Cosign Transform is applied in the first stage; later N level Discrete Wavelet Transform (DWT) is applied for reducing up to the size of the watermark image. The water mark image is inserted in LHn Sub band of the wavelet image using LSB concept. Simulation results show that the proposed technique produces better PSNR and similarity measure. The experimental results indicate that the present approach is more reliable and secure efficient.The robustness of the proposed scheme is evaluated against various image-processing attacks

Application of Taguchi approach and Utility Concept in solving the Multi-objective Problem when

The traditional Taguchi method is widely used for optimizing the process parameters of a single response problem. Optimizationof a single response results the non-optimum values for remaining. But, the performance of the manufactured products isoften evaluated by several quality characteristics/responses. Under such circumstances, multi-characteristics response optimizationmay be the solution to optimize multi-responses simultaneously. In the present work, a multi-characteristics responseoptimization model based on Taguchi and Utility concept is used to optimize process parameters, such as speed, feed, depthof cut, and nose radius on multiple performance characteristics, namely, surface roughness (Ra) and material removal rate(MRR) during turning of AISI 202 austenitic stainless steel using a CVD coated cemented carbide tool. Taguchi’s L8 orthogonalarray (OA) is selected for experimental planning. The experimental result analysis showed that the combination of higherlevels of cutting speed, depth of cut, and nose radius and lower level of feed is essential to achieve simultaneous maximizationof material removal rate and minimization of surface roughness. The ANOVA and F-tests are used to analyze the results.Further, the confirmation tests are conducted and the results are found to be within the confidence interval