Histogram-Based Detection of Tomato Maturity: A Preliminary Study

Authors

  • Nur Amalina Baharom Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, Malaysia
  • Fatma Susilawati Mohamad Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, Malaysia.
  • Azizah Abdul Manaf Department of Computer Science, Faculty of Computing and Information Technology, University of Jeddah, Faisaliyah Branch, Jeddah, Kingdom of Saudi Arabia

DOI:

https://doi.org/10.37231/myjcam.2018.1.2.21

Keywords:

color histogram, color model, tomato maturity, histogram technique

Abstract

Color is one of the most important features of images. Estimating the ripeness of fruits via color can be performed as it is the dominant feature in describing the information of image. However, each of color model has given different performance when used in experiment. This paper reports a preliminary study to identify the ripeness of tomato by extracting the color features and compute into Histogram based method. Histogram proposes the number of color intensities in ROI (Region of Interest) or a whole image to give more possibilities result. Histogram based techniques merely count the number or frequency of pixels in an image. The output value of color model will be used as an input to the classifier in future works. Similarity measures such as Euclidean distance, City Block, Manhattan distance or Histogram Intersection will be explored to calculate the image similarity rating.

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Published

2018-12-31

Issue

Vol. 1 No. 2 (2018): Malaysian Journal of Computing and Applied Mathematics

Section

Articles

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