Abstract

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Urban water demand is rapidly growing in India due to high growth in urban population and rapid industrialization. Meeting this demand is a big challenge for the urban planners in India. Incidentally, the large urban areas are experiencing faster growth in population, and most of them are in arid and semi arid regions, which are naturally water-scarce. As a result, water supplies from local water resources including aquifers are falling far short of the high and concentrated demands in most urban areas. Under such situations, these large cities have to rely on distant large reservoirs. The analysis of 302 urban centers shows that cities with larger population size have much higher level of dependence on surface water sources. Also, greater the share of surface water in the city water supplies, higher was the level of per capita water supply. Multiple regression models are estimated for Class I cities and Class II towns in India. The results show that Population Elasticity of Water Supply (PEWS) change with time and space-for Class I cities it was 1.127 in 1988, whereas that with respect to 1999 population is 1.289. It also shows that Class I cities have better water supply (PEWS is 1.127 in 1988 and 1.289 in 1999) than Class II towns (PEWS is 0.396 in 1988 and 0.675 in 1999). Given the structure and pattern of urban population S. Mukherjee (B) 2036 S. Mukherjee et al.growth, economic conditions and water demands, large reservoirs will have a much bigger role in meeting urban water supply needs.

Face perception is a very important component of human cognition. We can judge the person's mood and mental status through his/her expressions. In other words, the most expressive way human display emotion is through facial expressions. And hence facial expression recognition has become an active research area in the field of human computer interaction. The work in this paper concentrates on images having different illuminations and analyzes the performance of canny edge detection method with two classifiers, Euclidian distance and neural network. The results are tested on JAFFE (Japanese Female Facial Expression) database, available in public domain and IFE (Indian Facial Expression) database which is self created.

The automatic construction of large, high-resolution multi view image registration is an active area of research in the fields of image processing. Multiview image registration can be used for many different applications. The most traditional application is the construction of large aerial and satellite photographs from collections of images, construction of virtual travel etc. This proposed Automatic feature based image registration method does not allow any user interaction and perform all registration steps automatically. Here the matching points are found automatically using local feature detector i.e. harris corner detector which find invariant features using feature descriptors as oriented patches. For estimating homography between detected features of images to be registered, Homography estimator i.e. modified RANSAC (RANdom SAmple Consensus) algorithm, and direct linear transformation algorithm is used. Here features are located at Harris corners (new improved) in discrete scale-space and oriented using a blurred local gradient. To have better spatial distribution of features, adaptive non- maximal suppression algorithm is used.Feature matching are achieved using RANSAC which also uses DLT (Direct Linear Transformation) and warping is applied to achieve final registered image. This proposed algorithm can be applied for the series of images that may or may not be in the same alignment as per desired output image, thus mainly scaling, rotation and image transformation must be applied to get proper registered image.