GET THE APP

Comparing performance of classification algorithms to use fo | 98233
An International Journal

Agricultural and Biological Research

ISSN - 0970-1907
RNI # 24/103/2012-R1

Abstract

Comparing performance of classification algorithms to use for grading coffee’s raw quality by using image processing techniques

Muktar Bedaso, Million Meshesha and Chala Diriba*

This study tries to apply digital image processing techniques towards sample Coffee raw quality value grading. More specifically, this study emphases on comparing performance of classification algorithms to use for grading coffee raw quality by using image processing methods. To ease experimentation image processing phases are followed, including image acquisition, image preprocessing (image filtering and attribute selection), image analysis (segmentation, feature extraction and classification), and image understanding for raw quality image grading. Artificial Neural Network, support vector machine and K-Nearest neighbor classifiers on each classification parameter of morphology, color and the mixture of the two has been made. Experimental outcomes confirm that Artificial Neural Network classifier generated the highest performance of 89.45% accuracy as compared to support vector machine (with 83.75%) and K-Nearest neighbor classifier (with 77.85%). Thus, suitable selection of image processing and classification techniques paves the way for higher accuracy in the higher-level process for decision making.

Journal Hilights
  • Abstracting and indexing in renowned databases
  • Expert editorial team
  • Good Clinical Practice (GCP)
  • High quality articles
  • High visibility
  • Inclusion/Exclusion Criteria
  • Intention-to-Treat Analysis
  • International readership
  • Language editing
  • Membership
  • Online manuscript submission and tracking system
  • Rapid peer review process
  • Reprints of published articles
Journal is Indexed in:
  • BIOSIS Previews and Zoological Record which are part of the life sciences in Web of Science (WOS)
  • Euro Pub
  • Google Scholar
  • MIAR
  • Publons
Journal Flyer
Flyer
Google Scholar Citation Report
Citation image
Peer Review Process Check
Publon image
Top