Object Classification from Shape Detection

  • Pragya NagpalEmail author
  • Ankush Mittal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1057)


We evaluate the problem of object detection and classification based on a single model for five diverse classes. The class detection problem is implemented by enabling a method which detects the presence or absence of every shape-based model in every instance of a class. Low-level feature extraction is also performed to facilitate object categorization on one-dimensional information of the dataset. We compute the categorization performance for both the modalities in separate as well as combined representations to produce improved experimental results. The combined obtained solutions provide a classification of the object into the five classes. We have evaluated our approach on the ETHZ dataset and found that it performs with an accuracy of 88.2% in classification based on object detection.


Canny edge detection Image classification MPEG-7 Object classification Object detection Shape detection MPEG-7 Structural similarity Template matching 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Graphic Era Hill UniversityDehradunIndia

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