Ankur Choudhary

Schur decomposition and dither modulation: an efficient and robust audio watermarking technique

To protect the copyright for providing ownership in audio signal watermarking techniques are requisite. In this paper, a new robust audio watermarking algorithm is proposed, which is based on Schur decomposition and Dither modulation. In the Schur decomposition and Dither modulation based technique, watermark embedding is done using Dither modulation quantization which has a good performance in terms of imperceptibility, robustness and speed etc. Schur decomposition and Dither modulation is a blind audio watermarking technique which is robust against various attacks such as Additive White Gaussian Noise (AWGN), cropping, echoing, low pass filtering, requantization, resampling etc. The proposed technique has shown efficient and stable performance against various attacks and it is computationally faster.

Protecting video data through watermarking: A comprehensive study

Digital video watermarking is a technique developed to help in copyright protection of video files. Digital video files can be easily copied and shared among many people on the Internet. So, its extremely necessary to protect the copyright and ownership right of the video files with the help of digital watermarking. In this paper, we are presenting the comparative study of different video watermarking techniques by analysing their performances, time taken for watermarking, co-relation of the extracted watermark with the original one, and some other important factors.

Software reliability prediction modeling: A comparison of parametric and non-parametric modeling

Reliable softwares are the need of modern digital era. Failure nonlinearity makes software reliability a complicated task. Over past decades, many researchers have contributed many parametric / non parametric software reliability growth models and discussed their assumptions, applicability and predictability. It concluded that traditional parametric software reliability models have many shortcomings related to their unrealistic assumptions, environment-dependent applicability, and questionable predictability. In contrast to parametric software reliability growth models, the non-parametric software reliability growth models which use machine learning techniques or time series modeling have been proposed by researchers. This paper evaluates and compares the accuracy of 2 parametric and 2 non parametric software reliability growth models on 3 real-life data sets for software failures.

Script identification and language detection of 12 Indian languages using DWT and template matching of Frequently Occurring Character(s)

India is a diverse country with various cultural and traditional differences. There are more than 12 distinguished different languages in the country, viz., Hindi, Bangla, Marathi, Oriya, Tamil, Telugu, Assamese, Manipuri, Gujarati, Kannada, Malayalam, Panjabi, Nepali, Tibetan, Urdu, etc. Optical Character Recognition (OCR) of Indian Languages needs to be designed in such a way that it automatically identifies the language of the input document for further processing. There are many techniques which are already implemented, but the problem lies in identifying and detecting the correct language as some of the languages uses the same or similar script. For example, the Bangla script is used to write - Bengali, Assamese and Manipuri languages. Though the scripts can be distinguished using global technique, the problem with languages having similar script still exist. To deal with this problem, a robust wavelet transform cumtemplate-matching invariant to rotation, scale and translation technique is deployed to identify the script and detect the language of the document automatically.

Parameter Estimation of Software Reliability Model Using Firefly Optimization

This paper, presents an effective parameter estimation technique for software reliability growth models using firefly algorithm. Software failure rate with respect to time has always been a foremost concern in the software industry. Every second organization aims to achieve defect free software products, which makes software reliability prediction a burning research area. Software reliability prediction techniques generally use numerical estimation method for parameter estimation, which is certainly not the best. Local optimization, biasness and model’s parameter initialization are some foremost limitation, which eventually suffers the finding of optimal model parameters. Firefly optimization overcomes these limitations and provides optimal solution for parameter estimation of software reliability growth models. Goel Okumoto model and Vtub based fault detection rate model is selected to validate the results. Seven real world datasets were used to compare the proposed technique against Cuckoo search technique and CASRE tool. The results indicate the superiority of proposed approach over existing numerical estimation techniques.

A Digital Image Watermarking Technique Using Cascading of DCT and Biorthogonal Wavelet Transform

Modern communication technology facilitates easy transmission of multimedia content. But if copyright protection of multimedia data, prevention of illegal access, and rights of intellectual property are considered, so this field needs more attention of researchers. It is a very simple process to make a copy of the multimedia data, alter it, and then put it back for business profits. Digital watermarking techniques provide a solution for this issue, by embedding some information, which can be further used to claim the ownership of multimedia data. In this paper, a new algorithm for the watermarking of digital images is proposed by cascading of two frequency domain transform techniques, i.e., biorthogonal wavelet transforms (BWT) and discrete cosine transform (DCT). Proposed technique takes the approximation component of the biorthogonal transform of cover image and then applies DCT to embed watermark. Embedding of watermark data is done in middle frequency component by comparison-based correlation technique. Also, this technique has been analyzed and compared with the existing ones by applying various image attacks and subsequently measuring the results and proved to be fairly robust.

A secure and reliable video watermarking technique

In this paper, LWT (Lifting Wavelet Transform) and SVD (Singular Value Decomposition) is used to design a video watermarking technique. The video is divided into different scenes, and the last frame of each scene is selected for embedding watermark. A gray scale watermark is selected for this purpose. I have used Histogram Difference Method for dividing the video into scenes. Each RGB video frame is converted into YCbCr format, and then luminance part (Y) is taken for inserting the watermark. The LWT is applied on Y component of the video frame to decompose it into four sub parts (LL, LH, HL, HH). Then SVD is applied on the LL sub part which decomposes it into U, S, and V components. Finally watermark is also decomposed using SVD to get Sw, Uw and Vw. Then S component of the cover video frame is modified using Sw component of the watermark to embed the watermark in the cover frame. Then Inverse SVD and Inverse LWT are applied to get the final watermarked video frame. The Imperceptibility and robustness of the watermarking method is checked by applying some intentional attacks on the watermarked video frame. The results of the scheme are also compared with other existing video watermarking techniques to prove that the proposed scheme works better than other existing video watermarking schemes.

An effective approach for regression test case selection using pareto based multi-objective harmony search

Regression testing is a way of catching bugs in new builds and releases to avoid the product risks. Corrective, progressive, retest all and selective regression testing are strategies to perform regression testing. Retesting all existing test cases is one of the most reliable approaches but it is costly in terms of time and effort. This limitation opened a scope to optimize regression testing cost by selecting only a subset of test cases that can detect faults in optimal time and effort. This paper proposes Pareto based Multi-Objective Harmony Search approach for regression test case selection from an existing test suite to achieve some test adequacy criteria. Fault coverage, unique faults covered and algorithm execution time are utilised as performance measures to achieve optimization criteria. The performance evaluation of proposed approach is performed against Bat Search and Cuckoo Search optimization. The results of statistical tests indicate significant improvement over existing approaches.

Parameter estimation of software reliability growth models using Krill Herd Algorithm

The proposed approach put forward an effective estimation of the parameters for software reliability growth models with the help of Krill Herd Algorithm. The Software Reliability Growth model is considered to be incomplete, if the parameters of model are not known and are not validated over failure datasets. Many techniques are present for estimating parameters of model based on numerical estimation, but the scope of quality enhancement still remain open. The proposed Krill Herd Algorithm based approach outclasses the problems of numerical estimation. The proposed work is validated over four real-time datasets.

Efficient parameter estimation of software reliability growth models using harmony search

The primary challenge of software reliability growth model is to find the unknown model parameters that are used to validate on software failure dataset. Though, numerical estimation technique plays a vital role in parameter estimation of software reliability growth models, they are not optimal as they suffer from constraints sucha as sample size, biasing, and initialisation of parameters. In this study, a parameter estimation of software reliability growth model that utilises a variant of harmony search is proposed. Extensive experiments are conducted on seven different software datasets of varying complexity. A robust experimental setup is developed employing an orthogonal array and Taguchi method. Two-fold performance comparisons are performed. First, the authors tested their proposed approach against Cuckoo search and numerical method (least square estimation) considering mean square error and Theils statistics as a quality measure. Second, the authors applied statistical tests are performed that demonstrate the superiority of their approach over the others. The underlying motivation to conduct this study is to motivate researchers to utilise their approach for a better estimation of model parameters.