INFORMATION PAPER International Journal of Recent Trends in Engineering‚ Vol. 1‚ No. 2‚ May 2009 Edge Detection Techniques for Image Segmentation – A Survey of Soft Computing Approaches N. Senthilkumaran1 and R. Rajesh2 School of Computer Science and Engineering‚ Bharathiar University‚ Coimbatore -641 046‚ India. 1 senthilkumaran@ieee.org‚ 2kollamrajeshr@ieee.org logical reasoning[1]. It has been applied to image processing in many ways[19]. Segmentation aims at dividing pixels into similar
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International Journal of Scientific and Research Publications‚ Volume 2‚ Issue 4‚ April 2012 ISSN 2250-3153 1 Automatic Accident Detection via Embedded GSM message interface with Sensor Technology C.Vidya Lakshmi‚ J.R.Balakrishnan M.E Computer Science Engineering Anand Institute of Higher Technology‚ Affiliated to Anna University Abstract- An automatic alarm device for traffic accidents is introduced in this paper. It can automatically find a traffic accident‚ search for the spot and then send
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Brinke‚ L.‚ Porter‚ S.‚ & Baker‚ A. (2011‚ in press). Darwin the detective: Observable facial muscle contractions reveal emotional high-stakes lies. Evolution and Human Behavior. http://www.psychologicalscience.org/index.php/news/releases/lie-detection-misconceptions-pitfalls-and-opportunities-for-improvement.html
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An XSS scenario without the use of “Script” and <> Usually when testing for XSS vulnerabilities‚ we normally use the attack vectors <script>alert(111)</script> ‚ <body onload=alert(111)/> etc. If the developer has implemented a blacklist serverside validation for <> and script‚ we will not get satisfactory test results. But in some scenarios we can successfully demonstrate an XSS attack even without using the above mentioned vectors. This new scenario is mainly
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Nanotechnology in cancer prevention‚ detection and treatment Panimalar Engineering College C.L.Femi femi.fermi@gmail.com Panimalar Engineering College C.B.Kavitha hassinimanish@gmail.com Abstract: This paper is an overview of advances and prospects in application of nanotechnology for cancer prevention‚ detection and treatment. We begin with brief description of the underlying causes of cancer. Then we address preventive treatment‚ disease-time treatment‚ and diagnosis in the context of some
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RUNNING HEAD: CHANGE DETECTION Change Detection Iman M. Elramsisy The College of Staten Island of The City University of New York Change Detection Introduction Most people are unaware of the changes in their visual environments until attention is drawn directly to those minor changes. Individuals do not often detect changes because of the lack of attention or insignificance of the change. In order for an individual to notice a change like color‚ location and identity of an object
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Levels of Prevention The three levels of prevention in the community settings are; primary prevention‚ secondary prevention and tertiary prevention. With these three levels of prevention it helps the individual‚ the people and the community to attain better and good health. First the primary prevention‚ which focus mainly on health education‚ health promotion primary. This activity is concerned in preventing the specific illness or disease. The U.S. Preventative Services Task Forces’ Guide to
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Cancer Gene Detection 11/06/12 Laboratory Report Objective(s) – The purpose of this experiment is to help students gain an understanding of p53 tumor suppressor genes and its role in familial cancers. Also‚ we evaluated p53 in cancer. Hypothesis – If the DNA has bits and particles‚ which are p53 hotspots being cut‚ than that means that cancer has been detected. Techniques & Skills – The skills that are required for this laboratory experiment is that we must exercise extreme caution when
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Roset!feld Received October 23‚ 1974 Derivative operators such as the gradient and Laplacian have been used for many years to detect edges in pictures. This note points out a possible advantage of using combinations of such operators for edge detection. Isotropic derivative operators such as the gradient and Laplacian are commonly used [1 ] to detect edges in pictures. For digital pictures‚ these operators are approximated by finite differences; for example‚ if the neighborhood of point e
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tumor and calculate its area based on classifying the images. Death rate among people has been increased due to diseases like brain tumor. The brain tumor that can be identified by using image processing. The proposed system enables automatic detection of brain tumor through MRI. So our main objective is to study‚ analyze and enhance MRI Image from the existing algothrim. Certain traditional approach requires manually extracting the location where the tumor is build. Now a day’s automatic approach
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