Morfolojik Görüntü İşleme Tekniği ile Yapay Sinir Ağlarında Görüntü Tahribat Analizi

Abstract

Teknolojinin gelişmesine paralel olarak kamera sistemlerinde yüksek düzeyde kaliteyi öngören lensler tasarlanmıştır. Ancak bu lensler yapısal olarak her ne kadar görüntü kalitesinde başarılı olsalar da üzerinde tahribat meydana gelmiş görüntülerin ayırt edilmesinde herhangi bir ek özellik mevcut değildir. Esasen bu tür tahribatların giderilmesi için yapay zeka teknikleri kullanmak mümkündür. Bu çalışmada, yapay sinir ağları kullanarak üzerinde tahribat meydana gelmiş görüntülerin morfolojik görüntü işleme teknikleri ile birleştirilerek tahribatın derecesine göre orijinal görüntüye yakınsaması ele alınmıştır. Ayrıca bu amaca ulaşmak ve kullanımı kolaylaştırmak amacıyla geliştirilen arayüz sayesinde eğitim ve test verilerinin yanı sıra ağı oluşturmak için kullanılacak parametrelerin kolaylıkla hazırlanan algoritmaya entegrasyonu sağlanmaktadır.

 

Anahtar Kelimeler: Yapay Sinir Ağları, Karakter Tespiti, Morfolojik Görüntü İşleme

Image Damage Analysis With Morphological Image Processing Technique Using Artificial Neural Networks

Abstract

The lenses providing high quality for camera systems are designed as parallel with developing technologies. These lenses do not have any additional functionality to distinguish damaged images while they are successful with regard to image quality. Essentially, artificial intelligence techniques can be used to eliminate such damaged cases. In this study, convergence to original image of the damaged images according to the degree of damage using together artificial neural networks and morphological image processing techniques are discussed. Also, it is provided to be integrated training and test data with used algorithm thanks to developed interfaces to achieve goal and to facilitate use. In addition, this interface is used to be entered the training parameters to the system.

 

Keywords: Artificial Neural Networks (ANN), Character detection, Morphological image processing

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