STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Image Processing & Pattern Recognition Progress

Efficient Object Detection Based on Local Invariant Features

  1. Anand Rathod
  2. Manoj Bagale
  3. Dinesh Taral
  4. D. R. Pawar

Abstract

Object detection is an important task in image processing and computer vision. Binary Robust Invariant Scalable Keypoint (BRISK) local features are extracted from the object. These features are invariant to image scale, translation, rotation, illumination and partial occlusion. Object detection process begins by matching individual features of the user queried object to a database of features with different objects which are saved in advance. Cite this Article:Anand Rathod, Manoj Bagale, Dinesh Taral, D.R. Pawar. Efficient Object Detection Based on Local Invariant Features. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(2): 1–3p.

Keywords

Support