Görüntü analizi ile çıkarılan özelliklerden görüntü içeriğinin tahmini ve sınıflandırma
Classification and estimation of image content from feature extraction with image analysis
- Tez No: 120050
- Danışmanlar: YRD. DOÇ. DR. ZİYA TELATAR
- Tez Türü: Yüksek Lisans
- Konular: Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering
- Anahtar Kelimeler: Classification, Pattern Recognition, Artificial Intelligence, Neural Networks, Fuzzy Logic, Bulanık mantık, Görüntü analizi, Sinir ağları, Sınıflandırma, Yapay zeka, Classification, Pattern Recognition, Artificial Intelligence, Neural Networks, Fuzzy Logic, Image analysis, Nerve net, Artificial intelligence
- Yıl: 2002
- Dil: Türkçe
- Üniversite: Ankara Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Elektronik Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: Belirtilmemiş.
Özet
ABSTRACT Master Thesis CLASSIFICATION AND ESTIMATION OF IMAGE CONTENT FROM FEATURE EXTRACTION WITH IMAGE ANALYSIS Yusuf ÖZTÜRK Ankara University Graduate School of Natural and Applied Sciences Department of Electronics Engineering Supervisor: Asst.Prof.Dr.Ziya TELATAR In this work, many pattern rocognition techniques used to solve the classification problems were investigated. For this purpose, the implementations, performances, and advantages in artificial intelligence methods such as the neural networks and the fuzzy logic are presented. The developed algorithms were tested by dedecting the microcalcifications on the mammogram images. If a region contains microcalcifications then due to the impulsive nature of microcalcifications the symmetry of the distribution is destroyed. The dedection sheme was performed by using the previously obtained features training our system 2000, 60 pages
Özet (Çeviri)
ABSTRACT Master Thesis CLASSIFICATION AND ESTIMATION OF IMAGE CONTENT FROM FEATURE EXTRACTION WITH IMAGE ANALYSIS Yusuf ÖZTÜRK Ankara University Graduate School of Natural and Applied Sciences Department of Electronics Engineering Supervisor: Asst.Prof.Dr.Ziya TELATAR In this work, many pattern rocognition techniques used to solve the classification problems were investigated. For this purpose, the implementations, performances, and advantages in artificial intelligence methods such as the neural networks and the fuzzy logic are presented. The developed algorithms were tested by dedecting the microcalcifications on the mammogram images. If a region contains microcalcifications then due to the impulsive nature of microcalcifications the symmetry of the distribution is destroyed. The dedection sheme was performed by using the previously obtained features training our system 2000, 60 pages
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