In recent days, Whenever someone wants to take a book from library he or she has to go through all the books available in library related to the particular subject. Even if the book is not available in that library, the user will have to search the entire department. Also the manual work done by the librarians is tedious as they have to organise the books as per the department and also have to maintain the records To summarise the present day library system is not efficient and need improvement with the advance technology . To solve the problem of manual work done in the present day library system, we propose the idea of using a smart cart for accessing the library catalogue. It will automate the process of borrowing a book or issuing a book or any other literature available in library. We propose to use an intelligent system that reduces the manual work and fastens the processes in a library. Also we can merge the data- bases of various public libraries available in a particular city and provide the information to the citizens so that it will be easier for them to go to only that specific library which has the book instead of browsing through all the libraries and moving from place to place .
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.
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