Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

Authors

  • Maíla de Lima Claro Federal University of Piauí, Information Systems, Picos-PI, Brazil
  • Leonardo de Moura Santos Federal University of Piauí, Information Systems, Picos-PI, Brazil
  • Wallinson Lima e Silva Federal University of Piauí, Information Systems, Picos-PI, Brazil
  • Flávio Henrique Duarte de Araújo Federal University of Piauí, Information Systems, Picos-PI, Brazil
  • Nayara Holanda de Moura Federal University of Piauí, Information Systems, Picos-PI, Brazil
  • André Macedo Santana Federal University of Piauí, Information Systems, Picos-PI, Brazil

DOI:

https://doi.org/10.19153/cleiej.19.2.4

Keywords:

Classification, feature extraction, Glaucoma, segmentation

Abstract

The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classiffication of images in glaucomatous or not. We obtained results of 93% accuracy.

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Published

2016-08-01

Issue

Vol. 19 No. 2 (2016): Special issue devoted to CLEI 2015 (part 2)

Section

Articles

License

CLEIej is supported by its home institution, CLEI, and by the contribution of the Latin American and international researchers community, and it does not apply any author charges whatsoever for submitting and publishing. Since its creation in 1998, all contents are made publicly accesibly. The current license being applied is a (CC)-BY license (effective October 2015; between 2011 and 2015 a (CC)-BY-NC license was used).