EDGE DETECTION

Using Edge Detection to Solve Problems in Image Processing

Table of Contents

Introduction3

Analysis of Websites3

Evaluation and Rating for Sites4

Analysis of Software7

Analysis of Microsoft Visual Studio7

Edge Detection in MS Visual Studio8

Edge Detection With Matrix Convolution12

Designing the Kernel12

Analysis of Microsoft Access14

Analysis of PHP Software16

Image processing in PHP16

Image processing Requirement17

Processed Image example:17

Conclusion18

Using Edge Detection to Solve Problems in Image Processing

Introduction

The paper focuses on use of edge detection to solve problems in image processing, particular software and why these softwares would be best for the image processing application. In the first part of the paper the main focus is on the critical analysis of other similar image processing websites and their rating. For this section we selected and evaluated image processing websites. In second section the software we use for this project, i.e. Visual Studio and MS Access are discussed then analyzed and other software that could be used to develop this project such as PHP is discussed and analyzed.

Analysis of Websites

Image-based abstraction (or summarization) of a Web site is the process of extracting the most characteristic (or important) images from it. The criteria for measuring the importance of images in Web sites are based on their frequency of occurrence, characteristics of their content and Web link information (Bell, 1995, 1129-1159). As a case study, this work focuses on logo and trademark images. These are important characteristic signs of corporate Web sites or of products presented there.

The proposed method incorporates machine learning for distinguishing logo and trademarks from images of other categories (e.g., landscapes, faces). Because the same logo or trademark may appear many times in various forms within the same Web site, duplicates are detected and only unique logo, and trademark images are extracted. These images are then ranked by importance taking frequency of occurrence, image content, and Web link information into account. The most important logos and trademarks are finally selected to form the image-based summary of a Web site. Evaluation results of the method on real Web sites are also presented (Bell, 1995, 1129-1159). The method has been implemented and integrated into a fully automated image-based summarization system, which is accessible on following image-processing sites:

Evaluation and Rating for Sites

Image Processing Laboratory - Department of Informatics, University of Oslo: Mona Lisa. -->. Local activities. Courses. Research. Lectures and seminars. AIM (Applied and Industrial Mathematics). Local resources. People` Electronic documents. Software. Hardware. Other. Conference Calendars. [Link] http://www.ifi.uio.no/~blab/ (Rating: 5)

Computer Vision & Image Processing Group: Head: Professor I. Pitas. For statistics purposes please fill-in the fields below: Your full name: Your E-mail address: Reasons for accessing this WWW site: Brief profile. The digital image processing team at the. [Link] http://poseidon.csd.auth.gr/ (Rating: 4) - -

Software for Pattern Recognition and Image Processing Research: Below entries are given for finding software for pattern recognition and image processing. Suggestions for additions can be mailed to the below address. An unsorted list of mail messages found in discussion groups on these topics can be found. [Link] http://www.ph.tn.tudelft.nl/PRInfo/software.html (Rating: 4)

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