Paper Info
Title
Content-based objects detection for the recognition of building images
Abstract
This paper deals with content-based objects detection for the recognition of building images. The aim of this research is to develop a robust method by which the building images taken under different imaging conditions like view, illumination and scale can be recognized correctly. In the approach presented in this paper, the regions of objects like windows and wall are first detected from a building image based on their visual contents. Here, the segmentation of regions is done using color information and the regions of windows and wall are detected based on edge information and the location of regions. Then, some features like the proportions of width to height of windows and the invariant color features extracted from the region of wall are extracted for the robust recognition of building images. Finally, experimental results reveal the efficacy of the method proposed in this paper
Year
DOI
Venue
2001
10.1109/ICIP.2001.958591
ICIP (2)
Keywords
Field
DocType
color information,visual contents,content-based objects detection,recognition,invariant color features,scale,image segmentation,segmentation,building images,height,feature extraction,edge detection,walls,edge information,robust method,illumination,width,imaging conditions,windows,image colour analysis,view,data mining,lighting,image recognition,robustness,image retrieval
Computer vision,Image gradient,Scale-space segmentation,Pattern recognition,Object-class detection,Feature detection (computer vision),Computer science,Range segmentation,Feature (computer vision),Image texture,Image segmentation,Artificial intelligence
Conference
Volume
ISBN
Citations 
2
0-7803-6725-1
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Haomin Jin132.22
Masao Sakauchi2688149.27