Pustaka Ilmiah Universitas Padjadjaran

Abstrak

Implementing DEWA Framework for Early Diagnosis of Melanoma

This paper proposes a simple yet effective and integrated computer vision algorithm used for detecting and diagnosing the earlier stage of melanoma. The framework is built based on three steps of integrated multi aspect approach: segmentation, filtering and localization steps. In the first step, user can select several color spaces and apply leaning and non-learning methods to segment the object. In the filtering step, morphological filter has been applied for image noise removal. In the localization step, connected component labelling and K-means technique are used for objects classification. Type of cancer malignancy is determined based on a score calculated from ABCD characteristics. Experiment has been conducted successfully using skin cancer images taken from internet. This result proved that the developed framework can be used for supporting the early diagnosing of cancer. In general, this research can contribute to the computer science knowledge especially in field of computer vision.