LOCAL BINARY PATTERN METHOD AND FEATURE SHAPE EXTRACTION FOR DETECTING BUTTERFLY IMAGE

Authors

  • Dhian Satria Yudha Kartika
  • Darlis Herumurti
  • Anny Yuniarti

Keywords:

Local Binary Pattern, Image Processing, Classification, Butterfly Image, Feature Extraction

Abstract

Research in the field of information retrieval especially on image processing is proliferating.
Various methods are developed to be able to detect images optimally and produce better accuracy. The
process of image detection can use the dataset that exists around us. In this research, we use butterflies
dataset, since the butterfly has unique colors, patterns, and diverse shapes. Therefore, we use local binary
pattern method for texture feature extraction and region props for shape feature extraction. The results of
each texture feature extraction and shape feature extraction will be a merging process. The results of the
merging process get an accuracy of 66%. In addition, the system testing process with confusion matrix will
produce 67.1% precision value, 66% recall and f-measure of 66.5%. The merging process of both methods
shows the interplay of texture and shape extraction.

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Published

2018-04-29

How to Cite

Dhian Satria Yudha Kartika, Darlis Herumurti, & Anny Yuniarti. (2018). LOCAL BINARY PATTERN METHOD AND FEATURE SHAPE EXTRACTION FOR DETECTING BUTTERFLY IMAGE. GEOMATE Journal, 15(50), 127–133. Retrieved from https://geomatejournal.com/geomate/article/view/973