Paper Info
Title
Visual Investigation Using Circular Partitioning of Abstract Images
Abstract
This paper presents a novel approach for sketch-based image retrieval based on low-level features. The approach enables measuring the similarity be- tween a full color image and a simple black and white sketched query and needs no cost intensive image segmentation. The proposed method can cope with im- ages containing several complex objects in an inhomogeneous background. Two abstract images are obtained using strong edges of the model image and thinned outline of the sketched image. Circular-spatial distribution of pixels in the ab- stract images is used to extract new compact and effective features. The extracted features are scale and rotation invariant and tolerate small translations. The ma- jor contribution of the paper is in rotation invariance property of the proposed approach. A collection of paintings and sketches (ART BANK) is used for test- ing the proposed method. The results are compared with three other well-known approaches within the literature. Experimental results show signi£cant improve- ment in the Recall ratio using the proposed features.
Year
Venue
Keywords
2003
DICTA
color image,image retrieval,image segmentation
Field
DocType
Citations 
Computer vision,Invariant (physics),Pattern recognition,Image texture,Computer science,Image retrieval,Image segmentation,Pixel,Artificial intelligence,Invariant (mathematics),Color image,Visual Word
Conference
0
PageRank 
References 
Authors
0.34
17
3
Name
Order
Citations
PageRank
Abdolah Chalechale1737.12
Golshah Naghdy2299.36
Alfred Mertins353476.48