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Psoriasis is one of the most stressful skin diseases. The accurate assessment and effective management of the disease is one of the contributing factors in reducing the time required for relieving the disease symptoms. As the treatment is unusually subjective, an automatic and efficient computer aided assessment technique is an active area of research. In this study, we developed an automatic psoriasis...
Objective: To design the lip-color features and classification model and provide an automatic, quantitative method based on the lip detection in facial image. Methods: In this paper, We adopted the lip segmentation algorithm based on the three-dimensional mixture Skin Gaussian Model and color classification in SVM to solve this problem. Specifically, we used the GMM based iterations to confirm skin-color...
Melanomas are the most aggressive form of skin cancer. Due to observer bias, computerized analysis of dermoscopy images has become an important research area. One of the most important steps in dermoscopy image analysis is the automated detection of lesion areas in the dermoscopy images. In this paper, we present a deep learning method for automatic skin lesion segmentation. We use a subset of the...
Deep learning methods for image analysis have shown impressive performance in recent years. In this paper, we present deep learning based approaches to solve two problems in skin lesion analysis using a dermoscopic image containing skin tumor. In the first problem, we use a fully convolutional-deconvolutional architecture to automatically segment skin tumor from the surrounding skin. In the second...
Skin segmentation, which involves detecting human skin areas in an image, is an important process for skin disease analysis. The aim of this paper is to identify the skin regions in a newly collected set of psoriasis images. For this purpose, we present a committee of machine learning (ML) classifiers. A psoriasis training set is first collected by using pixel values in five different color spaces...
Sign language automatic recognition is an important research area with open challenges that aims to mitigate the obstacles in the daily lives of people who are deaf or hard of hearing and increase their integration in the predominantly hearing society in which we live. This paper implements, evaluates and discusses strategies for automatic recognition of Brazilian Sign Language (BSL) signs, which...
Potato as the fourth largest staple food in China, The external defect detection directly affects the industrialization of potato and deep processing. As the currently domestic testing method are mostly based on specific circumstances, specific light, which does not satisfy the testing requirements of actual environment. Therefore, this paper presents a non-destructive method for the study of green,...
The hand segmentation is the critical pre-processing of the gesture recognition application. Nowadays, to achieve a robust hand segmentation under cluttered background is still challenging. Advanced research in model-driven approach based on the depth information has obtained impressive performance. However, it is unable to deal with the hand very close to the body part. Also, a large number of marked...
Diabetic Foot Ulcer (DFU) is a major complication of Diabetes, which if not managed properly can lead to amputation. DFU can appear anywhere on the foot and can vary in size, colour, and contrast depending on various pathologies. Current clinical approaches to DFU treatment rely on patients and clinician vigilance, which has significant limitations such as the high cost involved in the diagnosis,...
In order to reduce the traffic accidents caused by fatigue driving, on the basis of analyzing the current fatigue driving detection methods, the fatigue state detection technology based on human eye state detection is studied. Based on the characteristics of skin color, the color space transformation of YCbCr is used to achieve face location to improve the efficiency of image processing. The binary...
Facial wearable items recognition refers to the judgment of whether the face in a face image wears a facial item, such as an eyeglass or a mask, which belongs to the category of face attribute analysis. In recent years, face attribute analysis mainly focuses on the study of gender, age, expression and other aspects, ignoring the study of facial wearable items recognition. However, this technology...
In this paper, we present an Optical Coherence Tomography (OCT) processing system to in vivo imaging of vascular remodeling of the skin. The main processing steps consist of vascular segmentation and vascular reconstruction. Firstly, image preprocessing algorithms, i. e., image enhancememt with mean filter and de-shadowing by projection-based strategies, are proposed for vascular segmentation. Then,...
The asymmetry of skin lesion is one of the three-point checklist (3PCLD). The 3CPLD is depending of a shape, hue/color and structure of the lesion. In the paper, a dermatological asymmetry measure in hue (DASMHue) is presented and discussed. The hue distribution asymmetry of the segmented skin lesion is discussed and new dermatological asymmetry measures of hue distribution are defined. One of the...
The proposed work describes an effective pipeline for skin lesion (nevus) analysis with related oncological outcomes. The increasing statistics of skin cancer have recently contributed to the development of new methods for early detection and discrimination of malignant skin lesions in order to drastically reduce the number of biopsies often very invasive for the patients. The main aggressive skin...
There are many people suffering from loss of hair or thinning hair. There are, however, no methods to quantitatively know their hair condition such as hair density and hair thickness without cutting the hairs. Our final target is to develop a system which enables general people to easily and quantitatively know their hair condition without cutting the hairs. As the first step, a method has been developed...
Computer Aided Diagnostic (CAD) tools for differentiating benign and malignant lesions are primarily of great importance. Most of the CAD tools employ a large and complex feature set. In this paper, a CAD system for classifying benign and malignant lesions using optimal feature set is proposed. The optimal feature set included the prominent color, shape and texture features. The feature set used is...
The overall aim of the proposed skin lesions classification method is to improve the quality and accuracy of existing skin diagnostic system by establishing superior feature extraction and classification of skin lesions from standard digital images. At first, images of skin lesions are pre-processed by resizing, removing hair, removing noise by filtering and enhancing contrast. Rather than using RGB/HSV/YCbCr...
Linea nigra (LN) is a linear hyperpigmentation of skin which can appear in men developing prostate cancer. Early diagnosis of such cancer can be made by image characterization. There generally exist low contrast between LN and surrounding areas in black skin images that influences segmentation accuracy. In this paper, this problem is addressed through a multispectral analysis of RGB color images using...
Melasma is a widely spread skin pigmentation disease and accurate assessments of the disease severity is crucial during its treatment. Recently, several computerized methods have been developed to overcome the shortcomings of the conventional clinical assessment method. As a key step in algorithm, image segmentation has extensive impacts on the accuracy of the assessment. Currently, the optimal hybrid...
This work presents the use of digital watermarking for applications of automated pigmented skin lesions assessment. Automated skin lesion assessment by digital image processing of macroscopic pigmented skin lesion (MPLS) images uses lesion characteristics for malignant risk computation. The accuracy of the computed risk level is increased when additional information is taken into consideration: age,...
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