Data Extraction from Computer Acquired Images of a Given 3D Environment for Enhanced Computer Vision and its Applications in Kinematic Design of Robos

Abstract

Problem statement: Literature review was mainly aiming at recognition of objects by the computer and to make explicit the information that is implicit in the attributes of 3D objects and their relative positioning in the 3D Environment (3DE) as seen in the 2D images. However quantitative estimate of position of objects in the 3DE in terms of their x, y and z co-ordinates was not touched upon. This issue assumes important dimension in areas like Kinematic Design of Robos (KDR), while the Robo is negotiating with z field or Depth Field (D_F). Approach: The existing methods such as pattern matching used by Robos for Depth Visualization (DV) using a set of external commands, were reviewed in detail. A methodology was developed in this study to enable the Robo to quantify the depth by itself, instead of looking for external commands. Results: The Results are presented and discussed. The major conclusions drawn based on the results were listed. Conclusion: The major contribution of the present study consists of computing the Depth (D¹) corresponding to the depth (d) measured from the photographic image of a 3DE. It had been concluded that, there exists an excellent agreement between the computed depth D¹ and the corresponding actual Depth (D). The percent deviation of D¹ from D (D_P) lies between ±2 over the entire region of the (D_F). Through suitable interfacing of the developed equation with the kinematic design of Robos, the Robo can generate its own commands for D_F negotiations.