Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Handwritten Syriac Character Recognition using Order Structure Invariance
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A string matching approach for visual retrieval and classification
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Graffiti-ID: matching and retrieval of graffiti images
MiFor '09 Proceedings of the First ACM workshop on Multimedia in forensics
Combining visual features and text data for medical image retrieval using latent semantic kernels
Proceedings of the international conference on Multimedia information retrieval
Central object extraction for object-based image retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
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Research of graffiti character recognition and retrieval, as a branch of traditional optical character recognition (OCR), has started to gain attention in recent years. We have investigated the special challenge of the graffiti image retrieval problem and propose a series of novel techniques to overcome the challenges. The proposed bounding box framework locates the character components in the graffiti images to construct meaningful character strings and conduct image-wise and semantic-wise retrieval on the strings rather than the entire image. Using real world data provided by the law enforcement community to the Pacific Northwest National Laboratory, we show that the proposed framework outperforms the traditional image retrieval framework with better retrieval results and improved computational efficiency.