Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection

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هند رستم محمد

Abstract

This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that the
proposedmethod obtained very good results but it requires more testing on different types of Skin
Cancer Images.

Article Details

How to Cite
“Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection”. Journal of the College of Education for Women, vol. 25, no. 2, Feb. 2019, https://jcoeduw.uobaghdad.edu.iq/index.php/journal/article/view/826.
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Articles

How to Cite

“Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection”. Journal of the College of Education for Women, vol. 25, no. 2, Feb. 2019, https://jcoeduw.uobaghdad.edu.iq/index.php/journal/article/view/826.

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