Advanced Image Processing for the Identification of Dermatological Diseases

Abstract

Skin diseases are a major health concern worldwide, especially in desert regions like Saudi Arabia, where they are more common. In spite of headways in clinical innovation, the expense and availability of diagnosing such circumstances stay huge boundaries. Our study proposes a cost-effective and effective approach to the detection of skin diseases, making use of cutting-edge image processing methods, in order to address this issue. Our methodology tackles the force of computerized picture examination, using promptly accessible gear like cameras and PCs. We simplify the identification procedure by combining image resizing with feature extraction via pre-trained convolutional neural networks. The accuracy of multiclass SVM classification is further improved, ensuring precise diagnosis for a variety of skin conditions. Through our creative system, we have accomplished an exceptional precision pace of 100 percent in recognizing three unmistakable kinds of skin sicknesses. Our system not only tells what kind of disease it is, but it also tells how it spreads and how bad it is, giving patients and doctors valuable information. SkinVision" is a ground-breaking innovation in dermatological diagnosis that provides quick, accurate results while sparing healthcare resources. We make skin disease detection accessible and effective in Saudi Arabia and elsewhere by combining cutting-edge image processing and computer vision techniques.