A Review on Global Thresholding Methods for Image Binarization

Yıl 2020, , 38 - 49, 26.10.2020

Abdullah Elen

https://doi.org/10.46387/bjesr.789534

Cited By: 3

Öz

Thresholding is one of the most essential issues in image processing. Although this technique is commonly used for segmentation of regions with different homogeneity in grayscale images, and it is also preferred for segmentation of colored images. In this study, 14 different algorithms capable of global thresholding on gray-scale images were categorized and examined in detail as cluster-based, entropy-based, shape-based and feature similarity-based. To test the performance of the algorithms, a dataset consisting of 15 different images was prepared. For these images, the threshold value was determined manually by four experts and reference binary images were obtained by calculating mean value. Accordingly, the binary images produced by each algorithm were examined with the similarity rates to the reference images using the Jaccard Index method. In experimental studies, it was seen that the highest score according to the average similarity ratio obtained belongs to the IsoData and Otsu algorithms with approximately 95%.

Anahtar Kelimeler

Image processing, Global thresholding, Binarization

Görüntü İkileştirme için Global Eşikleme Yöntemleri Üzerine Bir İnceleme

Öz

Görüntü işlemede en temel konulardan biri eşikleme yöntemidir. Bu yöntem, yaygın olarak gri tonlamalı görüntülerdeki farklı homojenliğe sahip bölgelerin bölütlenmesinde kullanılmakla birlikte renkli görüntülerin bölütlenmesi için de tercih edilir. Bu çalışmada, gri ölçekli görüntüler üzerinde global eşikleme yapabilen 14 farklı algoritma; kümeleme tabanlı, entropi tabanlı, şekil tabanlı ve öznitelik benzerliğine dayalı olmak üzere kategorize edilmiş ve detaylı olarak incelenmiştir. Algoritmaların performansını test etmek için 15 farklı görüntüden oluşan bir veri seti hazırlanmıştır. Bu görüntüler için dört uzman tarafından el yordamıyla eşik değeri belirlenmiş ve ortalama değeri alınarak referans ikili görüntüler elde edilmiştir. Buna göre her bir algoritmanın ürettiği ikili görüntüler, Jaccard Index yöntemiyle referans görüntülere olan benzerlik oranları incelenmiştir. Deneysel çalışmalarda, elde edilen benzerlik oranı ortalamasına göre en yüksek skor yaklaşık %95 ile IsoData ve Otsu algoritmalarına ait olduğu görülmüştür.

Anahtar Kelimeler

Görüntü işleme, Global eşikleme, İkileştirme

Kaynakça

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