Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Discrimination Using Fourier Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special memorial issue for Professor King-Sun Fu
Geometric invariance in computer vision
Geometric invariance in computer vision
Video and image processing in multimedia systems
Video and image processing in multimedia systems
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Machine learning and image interpretation
Machine learning and image interpretation
Computer and Robot Vision
Computer Vision
View Variation of Point-Set and Line-Segment Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modal Matching for Correspondence and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A visual search system for video and image databases
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Hybrid image segmentation using watersheds and fast region merging
IEEE Transactions on Image Processing
Invariant matching and identification of curves using B-splines curve representation
IEEE Transactions on Image Processing
EMSOFT '01 Proceedings of the First International Workshop on Embedded Software
An image based interactive digital library of mechanical engineering objects
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
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The search algorithms for the objects of interest related to shape similarity in a video or image library were implemented by various research groups. This work focuses on the search of a sample object (car) in video sequences and images related to the shape similarity. We also investigate a new description for cars, using relational graphs. The goal of this study is to investigate the shape matching method based on relational graph of objects with respect to its accuracy, efficiency and scalability. The aim is to annotate the images where the object of interest (OOI) is present. Then the query by text can be performed to extract images of OOI from a preprocessed database. The graph based description of the object with its meaningful parts provides an efficient way to obtain high level semantics from low level features. The hierarchical segmentation increases the accuracy of the detection of the object in the transformed and occluded images.