Browsing by Subject "Spatial informations"

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    Konuma bağlı uzamsal ilişkilerin biçimbilimsel modellenmesi
    (IEEE, 2007-06) Cinbiş, R. Gökberk; Aksoy, Selim
    Uzamsal bilgi, görüntü analizi modellerinde çok önemli bir yer tutmaktadır. Bu bildiride, ikili ve üçlü uzamsal ilişkileri bulmak için, matemaktiksel biçimbilim kullanarak, özelleştirilebilir, gerçekçi ve hızlı yöntemler öneriyoruz. Bu ilişkiler,resmin her noktasında, referans nesneye veya nesnelere göre, istenilen ilişkinin değerini veren bir matris hesaplanarak gösterilmektedir. Modelimiz, bir nesnenin istenilen yönlerden gözükmeyecek kısımlarını da dikkate almayı mümkün kılmakta, ayrıca, nesnelerin uzamsal olarak çok farklı olduğu durumlara da başarılı olmaktadır. Yapay ve gerçek görüntülerde yaptığımız deneyler ise modelimizin diğer yöntemlere olan üstünlüğünü ortaya koymaktadır. Spatial information plays a very important role in image understanding. Fuzzy mathematical morphology provides an effective basis for extracting binary and ternary spatial relationships by creating a fuzzy landscape where the value at each point corresponds to the relationship degree according to its position with respect to the reference object(s). We improve existing morphological approaches in terms of flexibility and efficiency while also obtaining more intuitive results. Our morphological definitions are sensitive to relative visibility of areas based on partial occlusions, and can also cope with the cases where some objects extend significantly differently relative to others. We show the effectiveness of the proposed definitions using synthetic and real images.
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    Relative position-based spatial relationships using mathematical morphology
    (IEEE, 2007-09-10) Cinbiş, R. Gökberk; Aksoy, Selim
    Spatial information is a crucial aspect of image understanding for modeling context as well as resolving the uncertainties caused by the ambiguities in low-level features. We describe intuitive, flexible and efficient methods for modeling pairwise directional spatial relationships and the ternary between relation using fuzzy mathematical morphology. First, a fuzzy landscape is constructed where each point is assigned a value that quantifies its relative position according to the reference object(s) and the type of the relationship. Then, the degree of satisfaction of this relation by a target object is computed by integrating the corresponding landscape over the support of the target region. Our models support sensitivity to visibility to handle areas that are partially enclosed by objects and are not visible from image points along the direction of interest. They can also cope with the cases where one object is significantly spatially extended relative to others. Experiments using synthetic and real images show that our models produce more intuitive results than other techniques. ©2007 IEEE.
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    Unsupervised tissue image segmentation through object-oriented texture
    (IEEE, 2010) Tosun, Akif Burak; Sokmensuer, C.; Gündüz-Demir, Çiğdem
    This paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use this information in defining its homogeneity measures, but it also uses it in its region growing process. This algorithm has been implemented and tested. Its visual and quantitative results are compared with the previous study. The results show that the proposed segmentation algorithm is more robust in giving better accuracies with less number of segmented regions. © 2010 IEEE.