SKIN TEXTURE RECOGNITION THROUGH IMAGE PROCESSING

2019 ◽  
Vol 6 (1) ◽  
pp. 17
Author(s):  
SHARMA SUKHDEEP ◽  
DUBEY AAYUSHI ◽  
◽  
Keyword(s):  
Image Processing ◽  
Texture Recognition ◽  
Skin Texture

Sa-Oiliness: A System to Measure Oiliness of Distant Subject Using Image Processing

2011 ◽  
Vol 403-408 ◽  
pp. 4462-4468
Author(s):  
Anand Gupta ◽  
Rachit Garg ◽  
Shruti Suri
Keyword(s):  
Image Processing ◽  
Medical Examination ◽  
Facial Skin ◽  
Dry Skin ◽  
Weighted Mean ◽  
Skin Texture ◽  
Skin Examination ◽  
Specific Instrument ◽  
Relative Value ◽  
Physical Presence

In medical examination of skin texture, an expert is generally needed to examine the skin texture thoroughly. It is felt that the same can be achieved through image processing, wherein a skin expert or physical presence of the patient are not needed on the spot. In the distant skin examination, expertise is required in analyzing the skin texture as appeared on the image. The texture is evaluated on the basis of oiliness of the skin, which is measured by a specific instrument [5]. As per our knowledge, the instrument is not readily available. To overcome this problem, a framework (SA-OILINESS) is proposed in this paper. It is designed so as to provide a scale to measure oiliness of facial skin through an image of a standard resolution. The proposed approach is based on the principle that the intensity of light from an oily skin is comparatively higher than that from a dry skin. Images of test subjects are taken at the same time and using the approach of weighted mean of the intensity of light reflected from the marked forehead region a scale of oiliness is developed. The scale is used to measure the relative value of oiliness.

Skin Texture Recognition using Medical Diagnosis

2010 ◽  
Author(s):  
Anindita Munshi ◽  
Ranjan Parekh ◽  
Swapan Paruya ◽  
Samarjit Kar ◽  
Suchismita Roy
Keyword(s):  
Medical Diagnosis ◽  
Texture Recognition ◽  
Skin Texture

Application of Fuzzy Closeness in Siberian Tiger Skin Texture Recognition

2012 ◽  
Vol 424-425 ◽  
pp. 415-419
Author(s):  
Jie Chen ◽  
Da Wei Qi ◽  
Xiu Juan Zhang
Keyword(s):  
Treatment Process ◽  
Experimental Results ◽  
Individual Identification ◽  
Texture Image ◽  
Texture Recognition ◽  
Skin Texture ◽  
Identification Method ◽  
Siberian Tiger ◽  
Standard Models

In order to improve the accuracy of tiger skin texture recognition, a skin texture identification method based on fuzzy closeness is put forward in this paper: four skin texture stripes extracted from a tiger texture image are selected as a research object. The image treatment process is: firstly, connected their endpoints to form three quadrilaterals, then regarded the quadrilateral area, bottom length, and left bottom corner features as the characteristics index of the object, the fuzzy closeness degree derived from the characteristics is compared with the standard models, and the final closeness degree is obtained. Experimental results show that this method can improve the accuracy of tiger skin texture recognition, and identify the tiger skin texture effectively to achieve individual identification of tigers finally.

A Look into Content-Based Image Search Engine System

2013 ◽  
Vol 756-759 ◽  
pp. 1576-1579
Author(s):  
Min Guo
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Information Retrieval ◽  
Search Engine ◽  
Future Development ◽  
Multimedia Database ◽  
Image Search ◽  
Texture Recognition ◽  
Current Image ◽  
Engine System

Image search engine technology is a combination of technologies of database, information retrieval, image processing and computer vision, texture recognition as well as multimedia database and network. This paper aims to present the flow chart of content-based image search engine system and explores the current image search technologies and its future development.

Information Sets and Information Processing

2011 ◽  
Vol 61 (5) ◽  
pp. 405 ◽  
Author(s):  
Madasu Hanmandlu
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Satellite Images ◽  
Noise Removal ◽  
Local Information ◽  
Natural Scenes ◽  
Global Information ◽  
X Rays ◽  
Skin Texture ◽  
Information Sets

<p>The area of image processing has made rapid strides because of enormous applications it has in different fields. This growth can also be attributed to the increasing use of fuzzy logic in all tasks of image processing as the fuzzy logic facilitates the representation of inherent uncertainty in the image information which can be local or global. For problems like enhancement global information is of interest whereas the local information is needed for the problems of edge detection, segmentation, and recognition. However we need both for the noise removal. The images are of varied types: Medical images (CT scans, MR, X-rays, ECG, etc.), satellite images, natural scenes, videos, games, multimedia, biometrics, industrial, astronomical so on and so forth. The approaches to tackle different images have to be different. For example skin texture can’t represented by a colour model.</p><p><strong>Defence Science Journal, 2011, 61(5), pp.405-407</strong><strong><strong>, DOI:http://dx.doi.org/10.14429/dsj.61.1192</strong></strong></p>

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

Analysis of the 9th November 1990 flare

2000 ◽  
Vol 179 ◽  
pp. 229-232
Author(s):  
Anita Joshi ◽  
Wahab Uddin
Keyword(s):  
Image Processing ◽  
Two Dimensional ◽  
Temporal Behaviour ◽  
Contour Maps ◽  
Dimensional Measurements ◽  
Processing Software ◽  
Image Processing Software

AbstractIn this paper we present complete two-dimensional measurements of the observed brightness of the 9th November 1990Hαflare, using a PDS microdensitometer scanner and image processing software MIDAS. The resulting isophotal contour maps, were used to describe morphological-cum-temporal behaviour of the flare and also the kernels of the flare. Correlation of theHαflare with SXR and MW radiations were also studied.

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