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ALT-BLOKLAR TEKNİĞİ VE KÜMELEME YÖNTEMLERİ İLE GÖRÜNTÜ BÖLÜTLEMENİN HIZLANDIRILMASI

ACCELERATING THE IMAGE SEGMENTATION USING SUB-BLOCK TECHNIQUE AND CLUSTERING METHODS

Journal Name:

  • Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

Publication Year:

  • 2014

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
In this study, it is aimed to use sub-block technique for the purpose of speeding up the segmentation of images within clustering algorithms. Due to the fact that all of the image data is given to clustering algorithms, generally the clustering process takes a lot of time, and it causes delays in real-time segmentation applications. In this study, in order to minimize the delays, the dividing of images into the sub-blocks, and using the average values of sub-blocks for the clustering process are proposed. As a result, the size of clustering data is relatively decreased. In the experimental studies, besides the images of travertine plates, well-known images such as “Lena” and “Baboon” were also used. The proposed method was compared with K-means, Fuzzy C-means, Kmedoids and Spectral clustering methods, and its speed increased 2-4 times. Furthermore, it was observed that the image quality did not change too much in case of small size of blocks.
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Abstract (Original Language): 
Bu çalışmada, kümeleme algoritmaları ile bölütlenen resimlerin daha hızlı bölütlenmesi için, alt-bloklama tekniğinin kullanılması amaçlanmaktadır. Genellikle, görüntü bilgisinin tamamının kümeleme algoritmalarına verilmesinden dolayı, kümeleme işlemi uzun sürmekte ve gerçek zamanlı bölütleme uygulamalarında gecikmeler olmaktadır. Bu çalışmada; gecikmeyi azaltmak için görüntü alt-bloklara ayrılarak, sadece alt-blok ortalamalarının kümelemeye sokulması önerilmektedir. Böylece kümeleme verisi oldukça azalmaktadır. Deneysel çalışmalarda traverten plaka resimlerinin yanı sıra, “Lena”, “Baboon” gibi bilindik resimler de kullanılmıştır. Önerilen yöntem, K-ortalamalar, Bulanık C-ortalamalar, K-ortaylar ve Spektral kümeleme yöntemleri ile kıyaslanmış ve 2-4 kat hızlanma sağlanmıştır. Blok boyutunun küçük tutulması durumunda görüntü kalitesinin çok fazla değişmediği de gözlenmiştir.
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