| Autor: |
Purnamawati, S, Rahmat, R F, Faza, S, Lumbantobing, A J |
| Zdroj: |
IOP Conference Series: Materials Science and Engineering; October 2019, Vol. 648 Issue: 1 p012027-012027, 1p |
| Abstrakt: |
Melanoma is one of the rare and malignant types of skin cancer. There are numerous ways to detect the melanoma, and one of them is through doctor diagnosis. A doctor can detect melanoma after a thorough medical check-up. If the patient has symptoms of melanoma, a biopsy will be carried out. This process requires a long time making it inconvenient. Therefore, an approach of the image processing system is necessary to assist the experts in diagnosing melanoma. The process consists of image input using the dermoscopy image, a pre-processing process of grey-scaling and median filtering, and feature extraction using Grey-Level Co-Occurrence Matrix (GLCM). In the final step, a classification process will be performed using learning vector quantization. Based on the experimental test, the system generated an accuracy of 83.33% in identifying melanoma cancer. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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