Journal of operating systems development & trends (vol1, issue2) by STM Journals Publication

May - August 2014 (JoOSDT)

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Dr. B.L. Shivakumar Professor Sri Ramakrishna Engineering College Coimbatore.

Shih-Ching Yeh Assistant Professor At National Central University Taiwan.

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STM JOURNALS

I take the privilege to present the print version for the Volume 1 Issue (2) of Journal of Operating Systems Development & Trends. The intension of JoOSDT is to create an atmosphere that stimulates creativeness, research and growth in the area of operating systems. The development and growth of the mankind is the consequence of brilliant Research done by eminent Scientists and Engineers in every field. JoOSDT provides an outlet for Research findings and reviews in areas of operating systems found to be relevant for National and International recent developments & research initiative. The aim and scope of the Journal is to provide an academic medium and an important reference for the advancement and dissemination of Research results that support high level learning, teaching and research in the domain operating systems. Finally, I express my sincere gratitude and thanks to our Editorial/ Reviewer board and Authors for their continued support and invaluable contributions and suggestions in the form of authoring write ups/ reviewing and providing constructive comments for the advancement of the journals. With regards to their due continuous support and co-operation, we have been able to publish quality Research/Reviews findings for our customers base. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra Director STM Journals

Journal of Operating Systems Development & Trends

Contents

1. A Novel Blind Restoration Technique using Different Edge Detection Methods Siddharth Saxena, Rajeev Kumar Singh

2. An Image Processing Algorithm for Varietal Classification of Sapota Fruits B. L. Benisha Bennet

3. Shell Implementation of Neural Net Over The UNIX Environment for File Management: A Step towards Automated Operating System Ankush Rai

Journal of Operating Systems Development & Trends Volume 1, Issue 2 www.stmjournals.com

A Novel Blind Restoration Technique using Different Edge Detection Methods Siddharth Saxena*, Rajeev Kumar Singh Department of CSE & IT, MITS, Gwalior, India Abstract Image restoration is a field of image processing in which we recover an original image from a degraded image. Objective of this paper is to compare different blurred and noisy images which are reconstructed with the help of blind deconvolution algorithm using different edge detection methods such as Canny, Sobel, Prewitt, Roberts, Laplacian. Initially original image is blurred using Gaussian filter. After that in the edges of blurred image ringing effect can be detected using different edge detection methods then it can be removed before restoration process. After that blind deconvolution algorithm is applied to get the reconstructed image. We used peak signal to noise ratio (PSNR) value for the comparison of different deblurred images. The higher the PSNR value, the better the image. Generally it is believed that blind deconvolution algorithm gives better result when there is no information about the distortion. It restores the image and point-speard function (PSF) at the same time.

Keywords: Blind deconvolution algorithm, edge detection methods, image restoration, PSF

Journal of Operating Systems Development & Trends Volume 1, Issue 2 www.stmjournals.com

An Image Processing Algorithm for Varietal Classification of Sapota Fruits B. L. Benisha Bennet* Department of ECE, Velammal College of Engineering and Technology (Affiliated to Anna Univ., Chennai), Madurai, India Abstract In several cases, fruits of different varieties are often mixed into the same bulk and reach the market/processing unit. In such scenarios, variations in product properties due to varietal variations result in inconsistent product end-product quality. This is of important concern in case of sapota; particularly between Cricket ball and P[ala varieties, the most dominant varieties grown in India. Hence, in the present study, a machine vision system consisting of a camera, illumination source, camera holding unit, sample platform, and computer was used to quickly differentiate between Cricket ball and Pala varieties of sapota fruit. The sphericity of the sample was used as the classification parameter. The developed image processing methodology gave an overall classification efficiency of around 95%.

Keywords: Machine vision, Image processing, Sphericity, Classification efficiency

Journal of Operating Systems Development & Trends Volume 1, Issue 2 www.stmjournals.com

Shell Implementation of Neural Net Over The UNIX Environment for File Management: A Step towards Automated Operating System Ankush Rai* Department of Applied Science, CRIAD Laboratories, Smriti Nagar, Bhilai, Durg, Chhattisgarh, India Abstract IT administrators goes through darn process of installing and managing operating systems (OS) with several patches on multiple servers by scripting which is achieved mostly for the deployment operations. Automating OS process like installation activities, configuration of hardware-settings, Indexing files, Sorting and managing other deliverables is what we present in this study with the help of scripting a neural net.

Keywords: Automated Operating System, Shell Scripting, Neural Net