Object Recognition Approaches

Abstract

Every Field of Computer Science from Robotics to Artificial Intelligence demand the system which have the ability like we human being have to recognize different things basis on certain properties of objects such as color, texture, shape etc. In this direction various algorithms have been implemented. The main motive of present work is to classify and analyze different object recognition techniques in an image for feature detection & extraction. The SURF (Speed Up Robust Feature) technique which rely on Integral images and Hessian Matrix for feature detection & extraction and ORB (Oriented Fast and Rotated BREIF) which is a combination of two major techniques: FAST (Features from Accelerated Segment Test) & BRIEF (Binary Robust Independent Elementary Features), both are best known technique for computer vision systems. Keeping this as a focal point, the work proposed aim at analyzing performance of the algorithms, which is particularly useful in mobile robots & Real world applications where it may encounter situations in which it has to recognize objects which may be at different orientations than the trained images

Authors and Affiliations

Preeti Saini

Keywords

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  • EP ID EP392539
  • DOI 10.9790/9622-0710024247.
  • Views 83
  • Downloads 0

How To Cite

Preeti Saini (2017). Object Recognition Approaches. International Journal of engineering Research and Applications, 7(10), 42-47. https://europub.co.uk/articles/-A-392539