Skin Lesion Classification using Raspberry pi

Skin Lesion Classification using Raspberry pi

Sindhu R Machakanur, Brundha R, Chihnitha B, Gaurav Satheesh Rai, Dr. Kavitha N

Department of Electronics and Communication Engineering,

RV Institute of Technology and Management,

Bengaluru, India

Abstract— The primary objective of this paper is to classify skin lesion by leveraging a range of diverse technologies. A skin lesion classification system employing deep learning and CNN technologies will be utilized to enable accurate and reliable identification and categorization of skin lesions, leveraging advanced image analysis techniques. The classification is of paramount importance as it aids in early detection and diagnosis of various dermatological conditions, enabling timely treatment and potentially saving lives. It is possible to accomplish that by integrating hardware and software. The utilization of Raspberry Pi offers a compact and cost-effective solution, enabling efficient deployment of the classification system in various settings, including remote or resource-limited areas. For the software component a program will be written python language, and this portion will be completed using Open CV. The objective of this classification is to accurately differentiate between benign and malignant lesions, enabling early detection and treatment of potential skin cancer cases.

Keywords Deep Learning, CNN, Raspberry pi, Open CV