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Support Vector Machine (Linear Kernel) and Interactive Genetic Algorithm-Based Content Image Retrieval Technique

  • Ankita DaymaEmail author
  • Amit Shrivastava
  • Aumreesh Kumar Saxena
  • Manish Manoria
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)

Abstract

Images are used to understand better and efficient services in many fields like crime prevention, government, hospitals, fashion and graphics, journalism. The popularity of the entire digital image tends to the huge amount of digital data in image database. It is difficult for the system to retrieve and search the query image from the large amount of data in database. This process takes a lot of time, and to overcome this problem Content-based image retrieval was introduced (CBIR). In CBIR, the image is searched or retrieved by sending the query image by the user and the visual feature extraction is done of the CBIR to retrieve the query image. The main ingredient of the proposed work is support vector machine along with the genetic algorithm. Here the chromosome is made differently. This work is implemented in MATLAB and calculates its performance.

Keywords

Support vector machine Genetic algorithm Content-based image retrieval Precision WANG image dataset 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Ankita Dayma
    • 1
    Email author
  • Amit Shrivastava
    • 1
  • Aumreesh Kumar Saxena
    • 1
  • Manish Manoria
    • 1
  1. 1.CSESIRTSBhopalIndia

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