By Ahmed H. Asad, Ahmad Taher Azar (auth.), Sabu M. Thampi, Ajith Abraham, Sankar Kumar Pal, Juan Manuel Corchado Rodriguez (eds.)
This ebook constitutes the completely refereed post-conference court cases of the second one overseas Symposium on clever Informatics (ISI 2013) held in Mysore, India in the course of August 23-24, 2013. The forty seven revised papers provided have been conscientiously reviewed and chosen from 126 preliminary submissions. The papers are equipped in topical sections on trend acceptance, sign and photo processing; information mining, clustering and clever details structures; multi agent structures; and machine networks and allotted platforms. The e-book is directed to the researchers and scientists engaged in quite a few fields of clever informatics.
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Additional resources for Recent Advances in Intelligent Informatics: Proceedings of the Second International Symposium on Intelligent Informatics (ISI'13), August 23-24 2013, Mysore, India
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Gaussian Color Model Using Combination of Two Color Spaces The third method uses the Gaussian model as a combination of two color spaces. This approach combines the advantages that can overcome the problems created when single color space is used. The basic goal of this approach is to find the combination of two color spaces that will efficiently classify the skin and non-skin pixels to produce human skin segmented region. In order to determine the effect on the detection of skin region this approach is used by using the concept of combination of color spaces along with the Gaussian model.
1007/978-3-319-01778-5_5, © Springer International Publishing Switzerland 2014 41 42 G. Rajaput and B. Reshmi (a) (b) (c) Fig. 1 (a) Retinal fundus image (b) Different sectors of retinal fundus image (c) Distribution of exudates around fovea region sufficient to detect DM. The distribution of these exudates around the fovea also must be considered. The exudates distribution around the fovea [2] is analyzed based on the retinal sectors (Fig. 1(b)). The retinal fundus image is sub divided into 10 sectors, namely,(1) Central; (2) Inner superior; (3) Inner temporal; (4) Inner interior; (5) Inner nasal; (6) Outer superior; (7) Outer temporal; (8) Outer inferior; (9) Outer nasal; and (10) Far temporal field, centered at the fovea center.
In [5] an algorithm for fovea detection based on optic disc diameter, a region of interest and adaptive threshold is described. An appearance based approach, in which the local contrast of the image is enhanced and the darkest region is selected as fovea candidate region, is presented in [6]. In [7], a method based on cost function as well as a point distribution model is proposed to detect and locate the fovea center. Hough transform based approach is presented in [8] for optic disc segmentation and for detecting fovea region and its center.
