Melanoma Detection in Dermoscopic Images using Color Features

Classification of Dermoscopic Images for the Detection of Melanoma

Disease classification is the crucial part of the medical diagnosis. Automated classification methodologies are highly recommended over manual methods so as to avoid the intra and inter observational errors. Image processing plays a vital role in making classification simple and accurate. Early detection of melanoma is very much essential as it is dangerous form of the skin cancer. By capturing...

Dermoscopic features of difficult melanoma.

BACKGROUND The dermoscopic diagnosis of cutaneous melanoma (CM) may be difficult because some CM lack specific dermoscopic features for melanoma diagnosis. OBJECTIVE To evaluate whether a diagnosis of CM could be achieved using the classic dermoscopic melanoma-specific criteria, we conducted a retrospective multicenter study of 508 CM samples. METHODS All the dermoscopic images were analyze...

The Mechanical Design of Drowsiness Detection Using Color Based Features

This paper demonstrates design and fabrication o f a mechatronic system for human drowsiness detection. This system can be used in multiple places. For example, in factories, it is used on some dangerous machinery and in cars in order t o prevent the operator o r driver from falling asleep. This system is composed of three parts: (1) mechanical, (2) electrical and (3) image processing system. A...

Face Detection in Color Images Using Primitive Shape Features

In this report, a novel face detection method is presented. Face detection is a primary step in many applications such as face recognition, video surveillance, human computer interface, and expression recognition. Many existing detection techniques suffer under scale variation, pose variation (frontal vs. profile), illumination changes, and complex backgrounds and sometimes have high computatio...

Streak-Detection in Dermoscopic Color Images using Localized Radial Flux of Principal Intensity Curvature