A NOVEL EDGE DETECTION METHOD USING K-MEANS CLUSTERING
الكلمات المفتاحية:
edge detection، clustering، image processingالملخص
In this paper, a new approach is introduced to detect the edges of any kind of grayscale image by using the k-means clustering algorithm, where three novel features are proposed by taking the advantage of the similarity of the image pixel with its eight surrounding neighbors through feeding these features as attributes to the clustering system. This method of edge detection does not use either any smoothing filter or threshold values. The experimental results show that an acceptable detection of the edges is done.
التنزيلات
Key Dates
منشور
2016-11-01
إصدار
القسم
Articles
الرخصة
هذا العمل مرخص بموجب Creative Commons Attribution 4.0 International License.
The Journal of Engineering and Sustainable Development is an open-access journal that all contents are free of charge. Articles of this journal are licensed under the terms of the Creative Commons Attribution International Public License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) that licensees are unrestrictly allowed to search, download, share, distribute, print, or link to the full texts of the articles, crawl them for indexing and reproduce any medium of the articles provided that they give the author(s) proper credits (citation). The journal allows the author(s) to retain the copyright of their published article.
Creative Commons-Attribution (BY) 
كيفية الاقتباس
Mohammed Khalaf, W. ., Al-Majdi, K., & Hashim Hamed, N. (2016). A NOVEL EDGE DETECTION METHOD USING K-MEANS CLUSTERING. مجلة الهندسة والتنمية المستدامة, 20(6), 207-215. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/709
