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The essence of an image is a projection from a 3-D scene onto a 2-D plane, during which the depth information is lost. The 3-D point corresponding to a specific image point is constrained to be on the line of sight. From a single image, it is very difficult to determine the depth information of various object points in an image. If two or more 2-D images are used, then the relative depth point of the image points can be calculated which can be further used to reconstruct the 3-D image by projecting the image points which includes the depth information as well. This paper presents two techniques namely binocular disparity and photometric stereo for depth calculation and 3-D reconstruction of an object in an image as it requires minimum user intervention.Binocular disparity method requires a pair of stereo images to compute disparity and depth to generate the desired 3-D view whereas the photometric stereo method requires multiple images under different light directions.

Recycling of engineering design is increasing exponentially in order to reduce the conceptual designing phase time due to rapid increase in technology. This leads to increase in frequent retrieval of the 3D models through web searching mechanism. So, it becomes a necessary challenge to design a 3D search engine which can search 3D models accurately as well as efficiently. The 3D searching is a technique developed to help the web users for extracting 3D models like complex engineering parts, various purpose graphical models, etc. The search engine takes input in the form of queries like text, 2D sketches, 3D sketches, 3Dmodel, 2Dmodel etc. When input queries is matched with the existing model in the database or similar model that are present in the database, the best multiple result is provided to user. This paper describes the basics of query by sketch which takes input by sketching manually with the aid of user interface. This input is normalized and further processed by Voxelization, Skeltonization and create Skeletal graph which is then mapped to database to extract best possible match. However, the main focus of this paper is to discuss the process of Voxelization method in very simple steps, as it plays a very important aspect in 3D searching.

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