Digital Image Processing

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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