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20 mit icle b rt u S A Applied Mechanics r International Journal of Electro Mechanics and u Mechanical Behaviour International Journal of Machine Design and Yo Manufacturing

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International Journal of Mechanical Dynamics and Analysis International Journal of Fracture and damage Mechanics International Journal of Structural Mechanics and Finite Elements

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Materials Processing ¬ International Journal of Mechanical Handling and

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Technologies « International Journal of Digital Electronics « International Journal of Digital Communication and Analog 5 more... Signals

Commercialization « International Journal of Environmental Chemistry « International Journal of Agrochemistry « International Journal of Prevention and Control of Industrial

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Planning « International Journal of Architecture and Infrastructure

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Image Processing & Pattern Recognition

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Electronics and Telecommunication « International Journal of Radio Frequency Design « International Journal of VLSI Design and Technology « International Journal of Embedded Systems and Emerging

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International Journal of Image Processing and Pattern Recognition

International Journal of International Journal of Image Processing and Pattern Recognition is a comprehensive journal that covers all the topics of image processing and recognition. All articles that are included in the journal are peer-reviewed and follow stringent guidelines before publishing. From image analysis to quadratic discriminate analysis all the topics fall under the scope and the focus of this journal.

Focus and Scope of the Journal  Image analysis  Image understanding  Digital image processing  Text compression  Still image compression  Video image compression  Feature extraction  Pattern recognition  Multi-scale signal analysis  Hidden markov models  Anisotropic diffusion  Partial differential equations  Self-organizing maps  Linear discriminate analysis  Quadratic discriminate analysis

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INTERNAL MEMBERS

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Commissioning Editors Ankita Singh

Dr. Chhavi Goel

Deepika Bhadauria

Manisha Dhoble Rekha Rani

EDITORIAL BOARD MEMBERS Dr. Xiaojun Chen chen Associate professor, Shanghai Jiao Tong University (SJTU), China

Dr. Mansaf Alam Department of Computer Science, Jamia Millia Islamia, New Delhi, India

Dr. Debnath Bhattacharyya Dept. of Computer Application, RCC Institute of Information Technology, Kolkata, India.

Dr. Hemanta Kumar Baruah Vice-Chancellor, Bodoland University Kokrajhar (Assam), India

Dr. Kiran Sree Professor in the department of CSE, NBKRIST, India

Dr. Tripty Singh Amrita School of Engg, Bangalore, India

Dr. A Devendran Associate Professor in Dr. M.G.R. Educational & Research Institute University (Deemed) Madurvoyal, Chennai, India

Dr. C Jayakumari Associate Professor, Department of Computer Application, SSN College of Engineering, Chennai, India

Dr. Sunil Kumar Department of Computer Science & Engineering College of Engineering and Technology, Mody University of Science and Technology, Lakshmangarh (Rajasthan), India

Dr. Sasmita Mishra Associate Professor Department of Comp. Sc. & Applications IGIT, Sarang Talcher, Dhenkanal, Orissa, India

Dr. Manish M Kayasth UCCC & SPBCBA & Udhna Academy College of Computer Application and IT, India

Bikram Ballav Assistant Professor, BPUT, Bhubaneswar, India

Ziyan Wu Research Scientist, Vision Solutions and Technologies, Siemens Corporate Research, Princeton (NJ), U.S.

Dr. Sanjeev Kumar Singh Associate Professor, Department of Mathematics, Union Christian College, RiBhoi, Meghalaya, India

Mr. Bhaskar Mandal Dept. of Computer Science and Engineering National Institute of Technology, Jamshedpur (JH), India

Prof Saurabh Rai Dhirendra Prasad DKTE Society's Textile and Engineering Institute, Ichalkaranji, India

Mr. S Sivakumar Periyar University, Salem, India

Mr. Saptarshi Roy Department of Electrical Engineering, NIT Warangal, India, India

Kalyan Kumar Jena Dept. of CSEA, IGIT, Sarang, Odisha, India,

Safar Irandoust Assistant Professor at University of Tabriz

EDITORIAL BOARD MEMBERS Shivkant Kaushik Assistant Professor, Jaipur Engineering College, India

Avatharam Ganivada Visiting Scientist, Indian Statistical Institute, Kolkata, India

Dr. Pokkuluri Kiran Sree Professor, Shri Vishnu Engineering College for Women, India

Mr. Kundan Lal Verma DDU Gorakhpur University, Gorakhpur, Uttar Pradesh, India

From the Editor's Desk Dear Readers, We would like to present, with great pleasure, the inaugural volume of a new scholarly journal, International Journal of Image Processing and Pattern Recognition. This journal is part of the Computer Science and Engineering, and is devoted to the scope of present Engineering issues, from theoretical aspects to application-dependent studies and the validation of emerging technologies. This new journal was planned and established to represent the growing needs of Image Processing and Pattern Recognition as an emerging and increasingly vital field, now widely recognized as an integral part of scientific and technical investigations. Its mission is to become a voice of the Computer Science and Engineering community, addressing researchers and practitioners in this area. The core vision of International Journal of Image Processing and Pattern Recognition in JournalsPub is to propagate novel awareness and know-how for the profit of mankind ranging from the academic and professional research societies to industry practitioners in a range of topics in Computer Science and Engineering in general. Journals Pub acts as a pathfinder for the scientific community to published their papers at excellently, well-time & successfully. International Journal of Image Processing and Pattern Recognition focuses on original high-quality research in the realm of Image analysis, Image understanding, Digital image processing, Text compression Still image compression, Video image compression, Feature extraction, Multi-scale signal analysis Hidden markov models, Anisotropic diffusion, Quadratic discriminate analysis. The Journal is intended as a forum for practitioners and researchers to share the techniques of Computer Science and Engineering and solutions in the area. Many scientists and researchers have contributed to the creation and the success of the Computer Science and Engineering community. We are very thankful to everybody within that community who supported the idea of creating an innovative platform. We are certain that this very first issue will be followed by many others, reporting new developments in the field of Computer Science and Engineering. This issue would not have been possible without the great support of the Editorial Board members, and we would like to express our sincere thanks to all of them. We would also like to express our gratitude to the editorial staff of JournalsPub, who supported us at every stage of the project. It is our hope that this fine collection of articles will be a valuable resource for Computer Science and Engineering readers and will stimulate further research into the vibrant area of Computer Science and Engineering. Puneet Mehrotra Managing Director

Contents 1. Using Image and Pattern Recognition to Play the Game of Connect Four Using Computer Punyajoy Saha

2. Brain Waves Can Be Used to Detect Potentially Harmful Personal Information Aryan Mathur

3. Enhancement K-Mean Algorithm (EKM) for Image Processing in MATLAB Himanshu Monga, Rubal Ahuja, Krishan Kumar

4. An Efficient Unconstrained Face Recognition System Based on Multimetric Learning L. Monisha, A. Kolappan

5. Analysis of Virtual or Remote Laboratories of IITs Ravi Kumar, Ankit Kumar1, Kapil Bhagat

International Journal of Image Processing and Pattern Recognition Vol. 2: Issue 2

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Using Image and Pattern Recognition to Play the Game of Connect Four Using Computer Punyajoy Saha* Indian Institute of Engineering Science and Technology, Shibpur, India

ABSTRACT Connect four is an advanced version of the commonly played game tic-tac-toe. Using an image recognition system, the computer can be assigned the current state of the play and using an algorithm the next move can be calculated. The extraction of image information and using it to find the solution of the diff condition is a fundamental in this field which is substantially extrapolated here. This paper is a result of our participation in a competition where we applied this concept with our robot and found quite suprising result. To play a game using a fully automated robot is a very interesting topic and this research is based on that. This entire project is done using Matlab. Keywords: algorithm, image recognition, robotics

INTRODUCTION The game of connect four is a hard game to solve even through many high ending learning algorithms. With that using an image recognition to identify the current game of play makes this topic of research even more interesting. Researches have been done extensively in both these field individually but a intermixing of two is a rare occurrence.[1,2] So this paper is a venture into the combination of both thus completing the totally automatic robot which can play the game of connect four and beat human players to an extent. This project is entirely based on Matlab tools and programming. LITERATURE REVIEW Connect Four as a Game Connect four is solved many times by many ways like in 1988, Vrije University, Netherland, Victor Allis in his paper ‘Knowledge based approach of connect four’ has showed a Shanon C-type problem solving approach where he

included nine strategies to solve the game of connect four. The paper clearly showed that white has higher chances of winning the game. Another famous strategy of solving this is by the minimax algorithm. In UC Berkley 2003 spring a paper was published by Amir Kamil, which shows the algorithm applied on the tic-tac-toe game which can be extended in connect four. Another paper named as ‘AI CONNECT FOUR’ was published in 2010 by Abe Karplus. He used the technique of ply depth to search for the correct solution of the game. Another paper named as ‘Artificial player for connect four’ by Allen Brubaker and Jason Long in December 2010, applied reinforcement training to create a viable artificial agent to solve this game.

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International Journal of Image Processing and Pattern Recognition Vol. 2: Issue 2

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Brain Waves Can Be Used to Detect Potentially Harmful Personal Information Aryan Mathur* Department of Science and Technology, IIMT College, Greater Noida, India

ABSTRACT A researcher is working to advance research to develop secure user authentication methods, by looking at using brain waves as individual identifiers. However, those brain waves can tell more about a person than just his or her identity, warns this expert. Keywords: brain, framework, information

INTRODUCTION Securing systems has gone past fundamentally thinking about a shrewd mystery key that could keep detestable PC authorities from hacking into your Facebook account. The more perplexing the system, or the more fundamental, private information that structure holds, the more moved the recognizing evidence system guaranteeing it gets the opportunity to be. Interesting finger impression compasses and iris recognizing evidence are just two sorts of acceptance methods, once considered as science fiction, that are in wide use by the most secure systems. Nevertheless, fingerprints can be stolen and iris scopes can be copied. Nothing has exhibited bonehead confirmation from being at risk to PC software engineers.[1]

“The fundamental dispute for behavioral, biometric approval is that standard techniques for affirmation, like a mystery word, confirm you once before you get to the organization,” said Abdul Serwadda a cybersecurity ace and accomplice educator in the Department of Computer Science at Texas Tech University.

“In no time, once you have gotten to the organization, there is no other course for the structure to regardless know it is you. The structure is outwardly debilitated concerning who is using the organization. So the scope of behavioral acceptance looks customer perceiving plans that can keep the system aware of the person who is using it. Through such cases, the system can screen some conviction metric about who may use it and rapidly incite for reentry of the mystery key at whatever point the sureness metric falls underneath a particular edge.” One of those examples, that is, developing in ubiquity inside the examination group is the utilization of cerebrum waves acquired from an electroencephalogram, or EEG. A few research gathers around the nation have as of late showcased frameworks which utilize EEG to verify clients with high exactness. Be that as it may, those mind waves can educate more regarding a man than simply his or her personality. It could uncover therapeutic, behavioral or passionate parts of a man that, if conveyed to light, could humiliate or harming to that individual.

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International Journal of Image Processing and Pattern Recognition Vol. 2: Issue 2

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Enhancement K-Mean Algorithm (EKM) for Image Processing in MATLAB Himanshu Monga*, Rubal Ahuja, Krishan Kumar Department of CSE, JCDM College of Engineering, Sirsa, India

ABSTRACT In this paper, a new segmentation scheme for the white blood cells from microscopic images is proposed. This is based on the K-means clustering technique. The RGB test images are converted to the L*a*b color space, and then the two color machinery (a and b) are used as features to the K-means clustering algorithm. The success of image analysis depends on segmentation reliability. The accurate partition of the image into regions is a challenging task. K-Means Clustering algorithm is the popular unsupervised clustering for dividing the images into multiple regions based on image color property. The major feature of the algorithm is that the user can specify the number of clusters- K, which is used to split the image into K regions. Keywords: image processing, K-mean clustering, segmentation

INTRODUCTION Clustering is a multivariate technique widely adopted in medical diagnostic studies, pattern analysis, image processing etc.[1] We divide the components of a dataset in a way that the ones having similar properties are allotted to cluster group.[2] Clustering can be seemed as optimization where the objective is to find the cluster solution according to some cluster validity measure [MSE, PSNR].[3] Clustering is one of the simplest techniques, and has been widely used in segmentation. And K means is one of the most popular and simplest methods for clustering schemes.[4] K-means clustering technique the RGB test images are converted to the L*a*b color space, and then the two color components (a and b) are used as features to the Kmeans clustering algorithm.[5] In this paper, the extended version of KM is

proposed, called the Enhanced KMeans (EKM) algorithm, which overcomes the KM weakness without limiting their preexisting capability (i.e. avoiding trapped center at local optimum location).[6,7] We divided the cluster images through the optimization images and comparisons among them with image matrices is represented by certain imagerelated quantities.[8] PROPOSED WORK The proposed EKM algorithm employs hard membership function as its clustering concept, where the data are clustered into non-overlapping regions. Consider an image, X with N data to be clustered into K regions. Initially, all centers values are randomly assigned. The i-th data, i v is assigned to the nearest data cluster, j c based on the minimum Euclidean

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International Journal of Image Processing and Pattern Recognition Vol. 2: Issue 2

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An Efficient Unconstrained Face Recognition System Based on Multimetric Learning L. Monisha*, A. Kolappan Department of Computer Science and Engineering, KNSK College of Engineering, Nagercoil, India

ABSTRACT This paper is basically proposed for reconstruction-based metric learning method to learn distance metric for unconstrained face verification. As compare to other metric (only helps for label information and do not applicable for reconstruction based metric) this metric id advanced. This metric is used for multiple metric learning to remove irrelavent data for recognition. Keywords: metric learning, RMML, unconstrained face recognition

INTRODUCTION For face recognition this metric technique is implicated for unconstrained images with various algorithm perceptions. For this technique almost 20 years of research was going and now a new technique came into know for the face recognition metric. Likewise biometric technique this is also a driving one to switch over on it. The problem to search a face among number of images is must. Over the past three decades, a large number of face recognition methods have been proposed in computer vision and most of them have achieved encouraging performance when face images were captured under controlled conditions. In many real world applications, human faces are usually captured in unconstrained environments and the performance of most existing face recognition methods drops heavily in this scenario because large intra-class variations caused by varying poses, illuminations, expressions, resolutions, expressions and backgrounds usually occur, which makes unconstrained face recognition more difficult and

challenging recognition.

than

controlled

face

Generally, face recognition can be categorized into two classes: face verification and face identification.

The first aims to verify whether a given pair of face images/video is from the same person or not, and the second aims to recognize the given face image/video from a gallery set and find the most matched one.

In this work, we focus on face verification, which aims to determine whether a given pair of face images/videos captured in unconstrained environments is from the same person or not.

From recent years lots of techniques can be came for the same but this metric technique is one of the successful technique till now (Figure 1).

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International Journal of Image Processing and Pattern Recognition Vol. 2: Issue 2

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Analysis of Virtual or Remote Laboratories of IITs Ravi Kumar1*, Ankit Kumar1, Kapil Bhagat2 1

Department of Electronics and Communication Engineering, Ganga Institute of Technology and Management, Kablana, Jhajjar, Haryana, India 2 Senior Software Architect, IBM, Auckland, New Zealand

ABSTRACT This paper is about virtual labs challenge of Ministry of Human resource development, authorities of India. The idea of virtual laboratory is to provide a danger to perform experiments the usage of the internet and visual aids without having the equipments at their quit. The digital lab software gives a completely unique opportunity to enhance the first-rate of engineering schooling, deepen information, and provide the necessary practical competencies to young minds through price effective outreach and distance getting to know sports. digital Labs is a undertaking initiated through the Ministry of Human resource development, government of India, below the national project on training via statistics and communique generation. The undertaking ambitions to provide remote-get entry to to Laboratories in diverse disciplines of science and engineering for students at all degrees from beneath-graduate to investigate. It additionally intends to broaden a whole getting to know management machine in which you can avail the various tools for studying, consisting of extra web-sources, video-lectures, animated demonstrations and self-assessment. there's also a issue in which expensive gadget and assets are shared, which are in any other case to be had to only a limited range of customers due to constraints on time and geographical distances. The challenge intends to cowl bodily sciences, chemical technological know-how and various branches of engineering like electronics and communications, computer technological know-how and engineering, electrical engineering, mechanical engineering, chemical engineering, biotechnology engineering and civil engineering. Keywords: digital, electronics, remote laboratories

INTRODUCTION It is miles quite hard to carry out actual time experiments in a few specialised regions of engineering, which require sophisticated equipments and skilled manpower. The unavailability of proper teachers with required information is any other bottleneck in this respect. The concept of digital laboratory is to provide college students a danger to carry out experiments using the internet and visual aids while not having the equipments at their cease. The RF and Microwave lab is a great candidate for digital laboratory because it requires high priced equipments including Ratiometres, community

Analyzers, Waveguides, Resonators and many others as well as professional and specialised employees, which most of the institutes cannot afford. The laboratory experience is manifestly an important a part of Engineering training, which goes a protracted way in constructing up desirable satisfactory engineers. The virtual lab application offers a completely unique possibility to enhance the great of engineering training, deepen understanding, and provide the necessary

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20 mit icle b rt u S A Applied Mechanics r International Journal of Electro Mechanics and u Mechanical Behaviour International Journal of Machine Design and Yo Manufacturing

Mechanical Engineering

¬ International Journal of Thermal Energy and

¬ International Journal of Production Engineering ¬ International Journal of Industrial Engineering

« « «

Applications

International Journal of Mechanical Dynamics and Analysis International Journal of Fracture and damage Mechanics International Journal of Structural Mechanics and Finite Elements

and Design ¬ International Journal of Manufacturing and

Materials Processing ¬ International Journal of Mechanical Handling and

Automation

Technologies « International Journal of Digital Electronics « International Journal of Digital Communication and Analog 5 more... Signals

Commercialization « International Journal of Environmental Chemistry « International Journal of Agrochemistry « International Journal of Prevention and Control of Industrial

Jul–Dec 2016

Pollution 1 more...

Civil Engineering

Planning « International Journal of Architecture and Infrastructure

Planning « International Journal of Rural and Regional Planning

« « « «

Development

« International Journal of Town Planning and Management

2 more...

Electrical Engineering

« « « «

Nursing

Material Sciences and Engineering

« « « «

5 more...

Biotechnology « International Journal of Industrial Biotechnology and « « « «

IJIPPR

Chemical Engineering « International Journal of Renewable Energy and its

Architecture « International Journal of Housing and Human Settlement

« « « « «

Image Processing & Pattern Recognition

5 more...

Electronics and Telecommunication « International Journal of Radio Frequency Design « International Journal of VLSI Design and Technology « International Journal of Embedded Systems and Emerging

« « « « «

International Journal of

Nanotechnology « International Journal of Applied Nanotechnology « International Journal of Nanomaterials and Nanostructures « International Journals of Nanobiotechnology

Chemistry

Physics « International Journal of Solid State Materials « International Journal of Optical Sciences