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2D Image Recognition of Partially Occluded Objects Based on Adaptive Window Positioning and Dynamic Time Warping

초록

영어

The boundaries of computer vision are especially challenged by partial occluded ob-ject recognition. In this paper, we proposed a new algorithm that used to recognize the partially occluded objects in 2-D images. Two different cases of occlusion are considered. Firstly, when an object missing some parts. Secondly, objects are overlapping each other. This approach uses contour of an object. Adaptive Window Positioning (AWP) uses to extract features from a contour. The proposed method uses the orientation field as fea-tures of the fragment. Dynamic Time Warping (DTW) works for matching and find the similarity between sub-images. As experiment result, the proposed recognition algorithm works without prior segmentation and robust to identify missing and overlapping objects and it can woks with strength occlusion.

목차

Abstract
 1. Introduction
 2. Proposed Algorithm for Occluded Object
  2.1. Dataset
  2.2. Contour Detection
  2.3. Features Extraction Using Adaptive Windowing Positioning (AWP)
  2.4. Compute Orientation in Window
  2.5. Matching Windows Using Dynamic Time Warping (DTW)
 3. Experimental Result
 4. Conclusion
 Acknowledgments
 References

저자정보

  • Mohammed Almuashi Research interests include Computer Vision, Image Processing and Multimedia Database.
  • Siti Z. Mohd Hashim Associate Professor at the De-partment of Software Engineering, Faculty of Computing, Universiti Teknologi Malaysia (UTM).
  • Dzulkifli Mohamad Senior professor in the Faculty of Computing Universiti Teknologi Malaysia (UTM) Johor Malaysia.
  • Mohammed Hazim Alkawaz Department of Information Science and Computing, Facul-ty of Information Sciences and Engineering, Management and Sci-ence University, Selangor, Malaysia.

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