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This work presents a novel approach for detecting and classifying melanocytic skin lesions on macroscopic images. We oversegment the skin lesions using superpixels, and classify independently each superpixel as a benign or malignant using local and contextual information. The overall superpixel classification results allow to calculate an index of malignancy or benignity for the skin lesion. Using...
It is challenging to develop an intelligent agent-based or robotic system to conduct long-term automatic health monitoring and robust efficient disease diagnosis as autonomous e-Carers in real-world applications. In this research, we aim to deal with such challenges by presenting an intelligent decision support system for skin lesion recognition as the initial step, which could be embedded into an...
Skin cancer is a deadly disease nowadays. So, early detection and prevention are essential. To classify the skin lesions in accurate manner an automatic Computer-Aided Diagnosis (CAD) for dermoscopy images were needed. The lesion segmentation is vital in the classification process. For segmenting the skin lesions many researchers have been developed different methods on melanocytic skin lesions (MSLs)...
Malignant melanoma is the deadliest form of skin cancer. In 2013 around 14,509 melanoma cases were found in the United Kingdom and the rate is increasing ever since. Melanoma can be easily treatable if detected in early stages. Clinical as well as automated methods are being used for melanoma diagnosis. Image-based computer aided diagnosis systems have great potential for early malignant melanoma...
Differentiation of pigmented skin lesions is difficult even for expert. In previous work, we proposed an algorithm for segmentation the dermoscopic images. In this paper, a feature extraction based algorithm is proposed which diagnose benignity or malignancy of the pigmented skin lesions in dermatoscopic images, to develop the previous work. In the proposed scheme the shape features are extracted...
Psoriasis severity assessment is usually performed based on the computation of the Psoriasis Area and Severity Index (PASI). Physicians subjectively classify the erythema parameter into several grades of severity. To support the decision and the evaluation of the psoriasis lesions' evolution in time, this study proposes an approach for the objective assessment of erythema degree. There were processed...
The aim of this study is to develop a method of lesion extraction from a large image of a skin surface and evaluate a new set of color features and their ability to classify the extracted skin lesions‥ It is beneficial for a dermatologist to be able to take a snapshot of a large skin surface and have an automated system locate and diagnose atypical lesions. The proposed system accomplishes this task...
One approach for deaf signs recognition and classification is presented in the paper. It is assumed that the signs are presented in digital images. Recognition algorithm is consisted of several stages. At the beginning it is necessary to perform appropriate image processing in sense of segmentation and filtration of the input images. Aim is to detect arm position, i.e. sign of interest. For this purpose...
Melanoma skin cancer accounts for less than 5% of skin cancer cases but causes the most deaths due to skin cancer. Convenient automated diagnosis of skin lesions and melanoma recognition can greatly improve early detection of melanomas. This paper presents a prototype of an image-based automated melanoma recognition system on Android smart phones. The system consists of three major components: image...
In this paper, the functional commands based on hand gesture are designed by Hu moments and contour sequence moments, which are invariant to the translation, rotation and scale of a hand gesture. First, the original image with a hand gesture is transformed into the color space of YCrCb. The segmentation of the skin-like objects is obtained by suitable thresholds of Cr and Cb. In sequence, the morphological...
Face Detection is the process of determining the face location, size and number. Robust face detection in complex background is a challenging task. In this paper, a novel method based on skin color segmentation and classification with fuzzy information granulation (FIG) for robust and fast face detection in color images is proposed. In this method, firstly we use skin color segmentation to extract...
We describe a system for automatic diagnosis of malignant melanoma based on digital dermoscopic images. The tool is designed for use with general practitioners, saving time and resources in the diagnostic process. A variety of indicative features are described mimicking the human approach for diagnosis. Segmentation, pattern recognition, and change detection are the important steps in our approach.
Computer aided diagnosis of dermoscopy images has shown great promise in developing a quantitative, objective way of classifying skin lesions. An important step in the classification process is the lesion segmentation. Many papers have been successful at segmenting melanocytic skin lesions (MSLs) but few have focused on non-melanocytic skin lesions (NoMSLs), since the wide variety of lesions makes...
Computer vision-based diagnosis systems have been widely used in dermatology, aiming at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumor. This paper proposes a novel clustering technique for the characterization and categorization of pigmented skin lesions in dermatological images. Appropriate image processing techniques (i.e. segmentation, border...
In this paper, an automatically skin cancer classification system is developed and the relationship of skin cancer image across different type of neural network are studied with different types of preprocessing.. The collected images are feed into the system, and across different image processing procedure to enhance the image properties. Then the normal skin is removed from the skin affected area...
In this paper, we propose an automatic system that executes hand gesture spotting and recognition simultaneously without any time delay based on Hidden Markov Models (HMM). Our system is based on three main stages; preprocessing, feature extraction and classification. In preprocessing stage, color and 3D depth map are used to detect hands. The hand trajectory will take place in further steps using...
Reflectance confocal microscopy is an emerging modality for dermatology applications, especially in-situ and bedside detection of skin cancers. Work to date has concentrated on hardware development and validation by clinicians in comparison with standard histological staining. As this technology gains acceptance, the development of automated processing methods becomes more important. We concentrate...
In this paper, an unsupervised algorithm, called the Independent Histogram Pursuit (IHP), for segmenting dermatological lesions is proposed. The algorithm estimates a set of linear combinations of image bands that enhance different structures embedded in the image. In particular, the first estimated combination enhances the contrast of the lesion to facilitate its segmentation. Given an N-band image,...
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