Boundaries object detection for skin cancer image using Gray-Level Co-Occurrence Matrix (GLCM)‎ and features minutiae points

Author

Muhammad, Hind Rustum

Source

al-Qadisiyah Journal for Computer Science and Mathematics

Issue

Vol. 7, Issue 1 (30 Jun. 2015), pp.1-10, 10 p.

Publisher

University of al-Qadisiyah College of computer Science and Information Technology

Publication Date

2015-06-30

Country of Publication

Iraq

No. of Pages

10

Main Subjects

Medicine

Abstract EN

In the present paper, Boundaries Object Detection for Skin Cancer Image using Connected Components is proposed.

We propose Connected Components algorithm which that capable of Segment with Extraction of connected boundaries for Skin Cancer Image Segmentation .

The algorithm is proposed to create a color label image using the local features minutiae points in skin cancer as objects image .

The performance of object Detection with Connected Components which are surround influence .

The proposed scheme can serve as a low cost preprocessing step for high level tasks such shape based recognition and image retrieval.

The experimental results confirm the effectiveness of the proposed algorithm.

American Psychological Association (APA)

Muhammad, Hind Rustum. 2015. Boundaries object detection for skin cancer image using Gray-Level Co-Occurrence Matrix (GLCM) and features minutiae points. al-Qadisiyah Journal for Computer Science and Mathematics،Vol. 7, no. 1, pp.1-10.
https://search.emarefa.net/detail/BIM-787776

Modern Language Association (MLA)

Muhammad, Hind Rustum. Boundaries object detection for skin cancer image using Gray-Level Co-Occurrence Matrix (GLCM) and features minutiae points. al-Qadisiyah Journal for Computer Science and Mathematics Vol. 7, no. 1 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-787776

American Medical Association (AMA)

Muhammad, Hind Rustum. Boundaries object detection for skin cancer image using Gray-Level Co-Occurrence Matrix (GLCM) and features minutiae points. al-Qadisiyah Journal for Computer Science and Mathematics. 2015. Vol. 7, no. 1, pp.1-10.
https://search.emarefa.net/detail/BIM-787776

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 9-10

Record ID

BIM-787776