An Automated Vision Based Change Detection Method for Planogram Compliance in Retail Stores

  • Muthugnanambika M.
  • Bagyammal T.
  • Latha Parameswaran
  • Karthikeyan VaiapuryEmail author
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 28)


Planogram are visual representations of a store’s products and services designed to help retailers ensure that the right merchandise is consistently on display, and that inventory is controlled at a level that guarantees that the right number of products are on each and every shelf. The main objective of this work is to propose an algorithm using image processing and machine learning as its base to find and detect the changes in the arrangement of objects present in the retail stores. The proposed algorithm is capable of identifying void space, count objects of similar type and thus helps in tracking the changes. Blob detection superseded by classification using a discriminative machine learning approach with the extracted statistical features of the objects has been used in this proposed algorithm. Experimental results are quite promising and hence this algorithm can be used to detect any changes occurring in a scene.


Blob detection Multiclass discriminative machine learning approach Change detection Planogram compliance 



We thank Amrita Vishwa Vidyapeetham for having provided the required resources in the Amrita-Cognizant Innovation Lab for carrying out the research work.


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Copyright information

© Springer International Publishing AG  2018

Authors and Affiliations

  • Muthugnanambika M.
    • 1
  • Bagyammal T.
    • 1
  • Latha Parameswaran
    • 1
  • Karthikeyan Vaiapury
    • 2
    Email author
  1. 1.Department of Computer Science and Engineering, Amrita School of EngineeringAmrita Vishwa VidyapeethamCoimbatoreIndia
  2. 2.TCS Innovation LabsChennaiIndia

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