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In this work we propose a novel method to calibrate the projector. Calibration of the projector deals with the calculation of geometric parameters of the projector which are intrinsic and extrinsic parameters. An un-calibrated camera assists the process of finding the geometric parameters for projector. This method exploits the fact that a projector can be treated as inverse camera. The camera captures the scene and saves it as an image while the projector projects an image on the scene. Camera to projector transformation is used to make the projector able to see the calibration pattern. Then the projector is calibrated in a similar fashion like camera. Real data is used to evaluate the proposed method of projector calibration and good results are obtained.

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e propose a holistic system to classify ancient Roman Republican coins based on their reverse-side motifs. The bag-ofvisual-words (BoW) model is enriched with spatial information to increase the discriminative power of the coin image representation. This is achieved by combining a spatial pooling scheme with co-occurrence encoding of visual words. We specifically address the required geometric invariance properties of image-based ancient coin classification, as coins from different collections can be located at differing image locations, have various scales in the images computer engineering from Myongji University, South Korea, where he also acted as a research assistant on a funded project related to the design and development of an intra-oral threedimensional scanner. He is currently pursuing his Ph.D. degree at the Computer Vision

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In this paper we proposed a method for geometric calibration of a projector. This method makes use of a calibrated camera to calibrate the projector. Since the projector works inversely with a camera i.e., it projects the image instead of capturing it, so it can be considered as a reverse camera. The projector is calibrated with the help of a calibrated camera using two types of chessboard, a printed chessboard and a projected chessboard by the projector. The object points of the projected chessboard pattern are measured with the help of calibrated camera and the image points are directly acquired from the chessboard pattern to be projected. Then using these object points and image points the projector is calibrated. Once the projector calibration is done, the transformation matrices (from projector to screen, from camera to screen and from camera to projector) are determined which are used for the reconstruction of the 3D geometry.

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