Color Channel Selection when Using Wavelet Ideology for Edge Detection in Color Medical Images Represented in RGB Space.
编号:34 访问权限:仅限参会人 更新:2025-11-19 09:20:25 浏览:1次 拓展类型2

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摘要
Medical visualization is a fundamental method that guarantees the accuracy of data analysis for the reliable and prompt diagnosis of potential diseases, resulting in improving the public health. Among the instruments of medical visualization, the methods for delineating edges and identifying possible regions of interest are notable. The proposed study examines color medical images of blood smears exhibiting megaloblastic anemia. To perform the requisite analysis, the input image is enhanced using histogram equalization and segmented into multiple color channels of the RGB format. The wavelet theory of the db1 mother wavelet is employed to identify edges in picture objects. The evaluation of the acquired results relies on visual comparison and widely recognized metrics: niqe, brisque, and entropy. The results indicate that decomposing the original image into data corresponding to distinct color channels yields greater information. For example, the value of the entropy parameter for individual color channels exceeds the value of this parameter for the image as a whole, which enhances the findings, both within the context of each color channel and in comparison, to the grayscale format, which is crucial for employing wavelet theory in image processing. The acquired information can be utilized based on the issue formulation necessary for diagnosing the ailment and making educated decisions.
关键词
color channel, color space, disease diagnostics, edge detection, medical image, region of interest, wavelet analysis
报告人
Kawthar Hamash
Assistant Professor Kennesaw state university

稿件作者
Vyacheslav Lyashenko Kharkiv National University of Radio Electronics
Diana Rudenko Kharkiv National University of Radio Electronics
Ling Shing Wong Thailand;Faculty of Health and Life Sciences; INTI -IU University; Nilai; Malaysia;Faculty of Nursing; Shinawatra University; Pathum Thani
jafar ababneh Jafar Ababneh Cyber Security department; Faculty of Information Technology Zarqa University Zarqa; Jordan jababneh@zu.edu.jo
Kawthar Hamash Kennesaw state university
Amer Abu-Jassar Department of Computer Science; College of Information Technology Amman Arab University Amman
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重要日期
  • 会议日期

    12月29日

    2025

    12月31日

    2025

  • 11月30日 2025

    初稿截稿日期

  • 12月30日 2025

    报告提交截止日期

  • 12月30日 2025

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