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Interest Point Detection Using Hough Transform and Invariant Patch Feature for Image Retrieval
Ahmad Nishat,안영은,박종안 한국ITS학회 2009 한국ITS학회논문지 Vol.8 No.1
This paper presents a new technique for corner shape based object retrieval from a database. The proposed feature matrix consists of values obtained through a neighborhood operation of detected corners. This results in a significant small size feature matrix compared to the algorithms using color features and thus is computationally very efficient. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. As the affine transformations preserve the co-linearity of points on a line and their intersection properties, the resulting corner features for image retrieval are robust to affine transformations. Furthermore, the corner features are invariant to noise. It is considered that the proposed algorithm will produce good results in combination with other algorithms in a way of incremental verification for similarity.
Image Feature Representation Using Code Vectors for Retrieval
Ahmad Nishat,조혜,박종안,박승진,양원일 한국ITS학회 2009 한국ITS학회논문지 Vol.8 No.3
The paper presents an algorithm which uses code vectors to represent comer geometry information for searching the similar images from a database. The comers have been extracted by finding the intersections of the detected lines found using Hough transform. Taking the comer as the center coordinate, the angles of the intersecting lines are determined and are represented using code vectors. A code book has been used to code each comer geometry information and indexes to the code book are generated. For similarity measurement, the histogram of the code book indexes is used. This result in a significant small size feature matrix compared to the algorithms using color features. Experimental results show that use of code vectors is computationally efficient in similarity measurement and the comers being noise invariant produce good results in noisy environments.
Image Retrieval Algorithm based on Incremental CBIR using Color Histogram
Waqas Rasheed,Nishat Ahmad,Ilhoe Jeung(정일회),SungKwan Kang(강성관),Jongan Park(박종안) 한국정보기술학회 2007 Proceedings of KIIT Conference Vol.2007 No.-
An incremental Content Based Image Retrieval (CBIR) method is proposed in this paper based on color histogram. Standard histograms, because of their efficiency and insensitivity to small changes, are widely used for content based image retrieval. But the main disadvantage of histograms is that many images of different appearances can have similar histograms because histograms provide coarse characterization of an image. We define an algorithm that utilizes the concept of Histogram Refinement [l] and we call it Color Refinement Method.