Comparison of Edge Detection Methods in Gray Images
The methods of edge detection play an important role in many image processing applications as edge detection is regarded as an important stage in image processing and the extraction of certain information from it.<br /> Therefore, this subject was the focus of many studies performed by many au...
| Main Authors: | , |
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| Format: | Article |
| Language: | Arabic |
| Published: |
Mosul University
2006-12-01
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| Series: | Al-Rafidain Journal of Computer Sciences and Mathematics |
| Subjects: | |
| Online Access: | https://csmj.mosuljournals.com/article_164056_6a93dfb7cf0b9f6d4e06e4d70acc2e23.pdf |
| _version_ | 1819027814804881408 |
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| author | Sobhi Hamdoun Afzal Hassan |
| author_facet | Sobhi Hamdoun Afzal Hassan |
| author_sort | Sobhi Hamdoun |
| collection | DOAJ |
| description | The methods of edge detection play an important role in many image processing applications as edge detection is regarded as an important stage in image processing and the extraction of certain information from it.<br /> Therefore, this subject was the focus of many studies performed by many authors. Many new techniques of edge detection which search into the discontinuity in color intensity of the image leading to the features of the image components were suggested.<br /> Despite of the presence of many methods of edge detection which proved their efficiency in certain fields and gave good results on application, the performance of one method differs from one application to another, thus there was a need to carry out an evaluation of performance for each method to show its efficiency. The aim of this research is to evaluate the performance of edge detection by choosing five methods known as (Canny, Laplacian of Gaussian,Prewitt, Scobel, Roberts) and the application of each method on images with grayscale to find out the performance of each of them and writing down computer programs for each. Also, a subjective evaluation to compare the performance of these five methods using Partt Figure of Merit, calculating the increase percent in the detected edges, decrease percent in the edge points and the correct position of the edge in each method.<br /> |
| first_indexed | 2024-12-21T05:48:27Z |
| format | Article |
| id | doaj.art-2813409c84f94cac8e49026ad19c70a8 |
| institution | Directory Open Access Journal |
| issn | 1815-4816 2311-7990 |
| language | Arabic |
| last_indexed | 2024-12-21T05:48:27Z |
| publishDate | 2006-12-01 |
| publisher | Mosul University |
| record_format | Article |
| series | Al-Rafidain Journal of Computer Sciences and Mathematics |
| spelling | doaj.art-2813409c84f94cac8e49026ad19c70a82022-12-21T19:14:03ZaraMosul UniversityAl-Rafidain Journal of Computer Sciences and Mathematics1815-48162311-79902006-12-0132112810.33899/csmj.2006.164056164056Comparison of Edge Detection Methods in Gray ImagesSobhi Hamdoun0Afzal Hassan1College of Computer Science and Mathematics University of Mosul, IraqCollege of Computer Science and Mathematics University of Mosul, IraqThe methods of edge detection play an important role in many image processing applications as edge detection is regarded as an important stage in image processing and the extraction of certain information from it.<br /> Therefore, this subject was the focus of many studies performed by many authors. Many new techniques of edge detection which search into the discontinuity in color intensity of the image leading to the features of the image components were suggested.<br /> Despite of the presence of many methods of edge detection which proved their efficiency in certain fields and gave good results on application, the performance of one method differs from one application to another, thus there was a need to carry out an evaluation of performance for each method to show its efficiency. The aim of this research is to evaluate the performance of edge detection by choosing five methods known as (Canny, Laplacian of Gaussian,Prewitt, Scobel, Roberts) and the application of each method on images with grayscale to find out the performance of each of them and writing down computer programs for each. Also, a subjective evaluation to compare the performance of these five methods using Partt Figure of Merit, calculating the increase percent in the detected edges, decrease percent in the edge points and the correct position of the edge in each method.<br />https://csmj.mosuljournals.com/article_164056_6a93dfb7cf0b9f6d4e06e4d70acc2e23.pdfimage processingedge detectiongray image |
| spellingShingle | Sobhi Hamdoun Afzal Hassan Comparison of Edge Detection Methods in Gray Images Al-Rafidain Journal of Computer Sciences and Mathematics image processing edge detection gray image |
| title | Comparison of Edge Detection Methods in Gray Images |
| title_full | Comparison of Edge Detection Methods in Gray Images |
| title_fullStr | Comparison of Edge Detection Methods in Gray Images |
| title_full_unstemmed | Comparison of Edge Detection Methods in Gray Images |
| title_short | Comparison of Edge Detection Methods in Gray Images |
| title_sort | comparison of edge detection methods in gray images |
| topic | image processing edge detection gray image |
| url | https://csmj.mosuljournals.com/article_164056_6a93dfb7cf0b9f6d4e06e4d70acc2e23.pdf |
| work_keys_str_mv | AT sobhihamdoun comparisonofedgedetectionmethodsingrayimages AT afzalhassan comparisonofedgedetectionmethodsingrayimages |