Abstract
This paper describes an approach to detect and analyze the properties of building in image. We use line segments and belongings in the appearance of building as geometrical and physical properties respectively. The geometrical properties are represented as principal component parts (PCPs) as a set of door, window, wall and so on. As the physical properties, color, intensity, contrast and texture of regions are used. Analysis process is started by detecting straight line segments. We use MSAC to group such parallel line segments which have a common vanishing point. We calculate one dominant vanishing point for vertical direction and five dominant vanishing points in maximum for horizontal direction. A mesh of basic parallelograms is created by one of horizontal groups and vertical group. Each mesh represents one face of building. The PCPs are formed by merging neighborhood of basic parallelograms which have similar colors. The wall regions of PCPs are detected. Finally, the structure of building is described as a system of hierarchical features. The building is represented by number of faces. Each face is regarded by a color histogram vector. The color histogram vector just is computed by wall region of face. The proposed approach was used to recognize a database containing 1005 images and 115 queried images. It has been confirmed with various kinds of images taken for different conditions like camera systems, weather and seasons
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