Title :
Recognition, segmentation and retrieval of gang graffiti images on a mobile device
Author :
Parra, A. ; Bin Zhao ; Joonsoo Kim ; Delp, Edward J.
Author_Institution :
Video & Image Process. Lab. (VIPER), Purdue Univ., West Lafayette, IN, USA
Abstract :
In this paper we describe three methods for recognition, segmentation and retrieval of gang graffiti images. The first method is color recognition based on touchscreen tracing, the second method is color image segmentation based on Gaussian thresholding and the third method is content based image retrieval. Our experimental results show an image retrieval accuracy of 92.8% for gang graffiti scene recognition and an image retrieval accuracy of 50.0% for gang graffiti component classification. The experiments also show an average image retrieval time of 0.56 seconds, from which the scoring process takes on average 984 microseconds.
Keywords :
Gaussian processes; content-based retrieval; image colour analysis; image recognition; image retrieval; image segmentation; mobile computing; touch sensitive screens; Gaussian thresholding; color image segmentation; color recognition; content based image retrieval; gang graffiti component classification; gang graffiti image recognition; gang graffiti image retrieval; gang graffiti image segmentation; gang graffiti scene recognition; image retrieval accuracy; mobile device; touchscreen tracing; Image color analysis; Image recognition; Image retrieval; Image segmentation; Training; Vocabulary; Color recognition; Gaussian thresholding; SIFT; content based image retrieval; image segmentation;
Conference_Titel :
Technologies for Homeland Security (HST), 2013 IEEE International Conference on
Conference_Location :
Waltham, MA
Print_ISBN :
978-1-4799-3963-3
DOI :
10.1109/THS.2013.6698996