| Abstrakt: |
Skin illnesses are more prevalent than other diseases. Skin disorders can be caused by a variety of things, including viruses, bacteria, allergies, and fungi. Thanks to advancements in laser and photonics-based medical technology, skin diseases can now be detected much more quickly and precisely. However, the expense of such a diagnostic is still very high. Therefore, image processing methods aid in the beginning development of automated dermatology screening systems. The classification of skin diseases relies heavily on the extraction of features. In a number of methods, computer vision plays a part in the identification of skin conditions. Skin infections are prevalent in Saudi Arabia as a result of the deserts and the hot climate. The study of diseases of the skin detection is aided by this work. We suggested a method for identifying skin conditions based on image processing. This technique uses analysis of images to determine the sort of disease after taking a digital photograph of the affected skin area. A digital camera and a personal computer are the only pricey pieces of equipment needed for our straightforward, quick method. The method uses a color image's inputs as its basis. Then, using a convolutional neural network that has already been trained, resize the picture in order to extract features. After that, a multiclass SVM was used to classify the feature. The user is then presented the results, which include the kind of disease, its distribution, and its severity. With a 100% accuracy rate, the system can accurately identify three different kinds of skin illnesses. [ABSTRACT FROM AUTHOR] |
