Informatics Publishing Limited

Kolla Bhanu Prakash ¹, M. A. Dorai Rangaswamy ², T. V. Ananthan ³, V. N. Rajavarman ³

Affiliations
1 Faculty of Computer Science Engineering, Sathyabama University, Chennai - 600 119, Tamil Nadu, IN
2 C.S.E & IT, AVIT, Chennai - 603104, Tamil Nadu, IN
3 Faculty of C.S.E, Dr.M.G.R.Educational & Research Institute, Chennai - 600 095, Tamil Nadu, IN

Abstract

Objectives: The objective is to develop a generic pixel-map based method to extract content in a short period of time for web documents. Method of Analysis: The method for extraction of content is in three levels, first level is in developing data inputs as attributes, second level in using the attributes to formulate a model and third level in interpretation of results. All three have variations so that validation comparison is possible for different parameters. Input data had all variations like language, script and usage and modeling is done using statistical, pattern recognition and ANN approaches. Findings: The method has demonstrated how quality and size of input data in the form of scalars, vectors and matrices affects the model and the result and this has been done for unstructured word sets chosen from web pages. The models chosen also give an idea of input/output variations in the outcome of the results. The uniqueness of the method is demonstrated for mono lingual, multi-lingual and transliterated datasets so that the applicability is universal. Novelty/Improvement: The method is generic in using pixel-maps, analytically stable in that the matrix input is used and versatility is demonstrated for adoption to different models.

Keywords

Data Mining Extraction, Image Processing Multilingual, Pre-processing, Segmentation, Unstructured

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M. Ramasubramanian ¹, B. Ponnambalam ², R. Latha ², M. A. Dorai Rangaswamy ¹

Affiliations
1 Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Missions University, Rajiv Gandhi Salai,(OMR),Paiyanoor-603104, Kancheepuram District, Tamilnadu, IN
2 Department of Computer Science and Engineering , Aarupadai Veedu Institute of Technology, Vinayaka Missions University, Rajiv Gandhi Salai,(OMR),Paiyanoor-603104, Kancheepuram District, Tamilnadu, IN

Abstract

3D shape reconstruction from 2D images is an inverse problem, and is therefore mathematically ill-posed. One solution to 3D shape reconstruction problem is to use a model based approach. This paper presents an analysis by synthesis method for solving 3D face reconstruction problems using anatomical landmarks and intensity from 2D frontal face images.

To improve the quality of 3D shape reconstruction we incorporate a number of steps in analysis by synthesis framework. Firstly, we approach the 3D model construction problem by using rigid and non rigid surface registration. Secondly, we simplify the shape estimation by using multidimensional amoeba optimization to optimize shape parameters while mapping texture directly using 3D-2D alignment. Thirdly, we evaluate the quality of the 3D shape reconstruction in the context of 3D shape error as well as by visual analysis.

Keywords

3D Face Database, Statistical Shape Modeling.

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D. Beulah David ¹, M. A. Dorai Rangaswamy ², M. Ramalatha Marimuthu ³

Affiliations
1 Sathyabama University, Chennai, IN
2 Department of CSE, Aarupadai Institute of Technology, Chennai, IN
3 Department of IT, Kumaraguru Institute of Technology, Coimbatore, IN

Abstract

This paper proposes an analog Hopfield neural network (HNN) for automatic image change detection problem between the images taken at two different exposure times. This optimization relaxation approach differs from other techniques in that it provides the strength of the change rather than assigning binary labels (changed/unchanged) to each pixel. By subtracting both images pixel by pixel, a difference image is obtained. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed or unchanged. An energy function is derived, so that the network converges to stable state. The main drawback of existing binary labeling approaches is that pixels are labeled according to the information supplied by its neighbors, where its self information is ignored. The main contribution of the analog Hopfield’s model is that it allows a tradeoff between the influence of a pixel’s neighborhood and its own criterion. This is mapped under the energy function to be minimized. Also a comparison between analog and discrete HNN shows similar Percentage of Correct Classification (PCC) and Yule values. However, the analog counterpart describes the degree of change by embedding both Spatial-Contextual Information and Self-Data Information.

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B. Padhmavathi ¹, P. Nirmal Kumar ², M. A. Dorai Rangaswamy ³

Affiliations
1 Department of Information Technology, Meenakshi College of Engineering, Chennai - 078, IN
2 Department of Electronics & Communication, College of Engineering, Guindy, Chennai – 025, IN
3 Department of Computer Science, AVIT, Vinayaka Mission University, Chennai, IN

Abstract

The growing possibilities of modern communications require a special means of confidential and intellectual property protection against unauthorized access and use. Cryptography provides important tools for the protection of information and they are used in many aspects of computer security. This paper makes use of encrypted secret sharing to increases the security level of hidden data and to provide Mutual Authentication of the users. The visual cryptography scheme is a perfect secure method that encrypts a secret image by breaking it into shadow images. A distinctive property of visual cryptography scheme is that one can visually, without computation, decode the secret by superimposing shadow images. The property of visual secret sharing in reversible style provides more security. This method not only can fast decode without causing pixel expansion but also increase the secret-hiding ratio. Random-Grid Algorithm is used to create secret shares without pixel expansion. This paper extends the capabilities of the Visual Cryptography as a mere secret sharing technique to a Novel Mutual Authentication provider. If one stacks two transparencies(shares) together straightforwardly, a secret image will appear. Stacking two transparencies after reversing one of the transparencies, another secret image will unveil. An attempt is made to provide two transparency three-way mutual authentication by using Visual cryptography in the reversible style.  

Keywords

Visual Cryptography in Reversible Style, Pixel Expansion, Random Grid Algorithm, Secret Transparencies, Share Stacking.

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Puja Kumara Singh ¹, M. A. Dorai Rangaswamy ¹

Affiliations
1 Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Missions University, IN

Abstract

The main aim of the project is to develop an ERP product for requirement based testing of sales management system which will manage the customer details, warehouse, sales quotation, sales order, sales details and product details.

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M. Ramasubramanian ¹, M. A. Dorai Rangaswamy ¹, Hema Prabha ¹, A. Dilipan ¹

Affiliations
1 Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Missions University, Rajiv Gandhi Salai,(OMR), Paiyanoor 603104, Kancheepuram District, Tamilnadu, IN

Abstract

In this paper we present a system that automatically generates 3D face model from a single frontal image of a face with a generic 3D model. Our system consists of three components. The first component detects features such as eyes, mouth, eyebrows and facial contour. After detecting the second component is automatically adjusted.

The general model of 3D face model in 3D using special geometric transformations. Once the model is almost six basic facial expressions are generated using MPEG - 4 facial animation parameters (SPF). To generate transitions between these facial expressions we use 3D shape morphing between the corresponding face models and textures blending relevant. Our system has the advantage that it is fully automatic powerful and fast. It can be used in a variety of applications from depth is not critical, such as games, avatars, etc. Our results show facial recognition system accuracy Morphing. We have tested and evaluated using a database bu-3DFE.

Keywords

Generic 3d Model, Morphing, Animation, Texture etc.

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A. Maheshwari ¹, M. A. Dorai Rangaswamy ²

Affiliations
1 Sathyabama University, Chennai, IN
2 Department of CSE, AVIT, Chennai, IN

Abstract

Turing Machines are the most powerful computational machines. Turing machines are equivalent to algorithms, and are the theoretical basis for modern computers. Still it is a tedious task to create and maintain Turing Machines for all the problems. The Universal Turing Machine (UTM) or simply a universal machine is a solution to this problem. A UTM simulates any other TM, thus providing a single model and solution for all the computational problems. The creation of UTM is very tedious because of the underlying complexities. Also many of the existing tools do not support the creation of UTM which makes the task very difficult to accomplish. Hence a Universal Turing Machine is developed for the JFLA Platform. JFLAP is most successful and widely used tool for visualizing and simulating all types of automata.

Keywords

CFG, Delta Rule, FSA, PDA, JFLAP, Transitions, UTM.

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Kolla Bhanu Prakash ¹, M. A. Dorai Rangaswamy ¹

Affiliations
1 Faculty of Computer Science Engineering, Sathyabama University, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai - 600119, Tamil Nadu, IN

Abstract

Objectives: The amount of information available on web today is more than at any point in history, and greater challenges arouse due to this huge wealth of information available. Also to deal with this information overload, challenging tools are required. Method of Analysis: Internet in the present day especially in India is spreading both in rural and urban areas. Bilingual and Multilingual websites are increasing to a larger extent. Even websites are becoming multitasking. Our main problem is to deal with multilingual web documents and ancient documents. Because, content extraction becomes difficult when such documents are considered. The present paper proposes a neural network approach and attribute generation to justify the content extraction studies for multilingual web documents. Findings: Results obtained are well defined and a thorough analysis is done. Novelty/Improvement: The method is versatile in using pixel-maps, analytically stable in that the matrix input is used and is demonstrated for adoption to different models.

Keywords

Attribute, Content Extraction, Mining, Multi-Lingual, Neural Network, Pattern, Pixel.

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