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Accurate and efficient shape matching approach using vocabularies of multi-feature space representations

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Abstract

Selection of compressed, robust and accurate features is the fundamental ingredient of effective content-based image recognition and retrieval using shape information of objects in the image. In this paper, we present a four-stage system for real-time object recognition and retrieval that employs multiple feature space representation using contour information. In the first stage, we pre-process the shapes to cater for the presence of distortions such as cracks that can significantly distort the contour information of the shape. We then generate multiple feature space representations of shapes to be used later in proposed combination for efficient and accurate retrieval of shapes using a hierarchical indexing structure. To enable real-time image-based shape analysis by enhancing the efficiency and reducing the storage requirement of proposed shape descriptors, we present a quantization approach to generate vocabulary of feature space representation of shapes. These features are then combined in an ensemble for accurate and efficient shape retrieval and recognition in the presence of large shape datasets. The proposed system is evaluated using publicly available shape datasets such as MPEG 7, Swedish leaf and KIMIA 99 datasets. Our approach achieves higher accuracies which are better than state-of-the-art approaches reported in literature whilst looking at a small subset of shapes in dataset.

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  1. Available at: http://www.cs.ucr.edu/eamonn/shape/shape.html.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A1A2061978).

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Authors and Affiliations

  1. Department of Computer Engineering, Bahria University, Islamabad, 44000, Pakistan

    Shehzad Khalid & Sadaf Sajjad

  2. Department of Computer Science, COMSATS Institute of Information Technology, Sahiwal, 44000, Pakistan

    Sohail Jabbar

  3. Department of Computer Science, Bahria University, Islamabad, 44000, Pakistan

    Sohail Jabbar

  4. Department of Industrial Security, College of Business and Economics, Chung-Ang University, Seoul, Korea

    Hangbae Chang

Authors
  1. Shehzad Khalid
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  2. Sadaf Sajjad
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  3. Sohail Jabbar
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  4. Hangbae Chang
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Correspondence to Shehzad Khalid.

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Khalid, S., Sajjad, S., Jabbar, S. et al. Accurate and efficient shape matching approach using vocabularies of multi-feature space representations. J Real-Time Image Proc 13, 449–465 (2017). https://doi.org/10.1007/s11554-015-0545-z

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