Title :
Content-based image retrieval of Web surface defects with PicSOM
Author :
Rautkorpi, Rami ; Iivarinen, Jukka
Author_Institution :
Lab. of Comput. & Inf. Sci., Helsinki Univ. of Technol., Espoo, Finland
Abstract :
This work describes the application of PicSOM, a content-based image retrieval (CBIR) system based on self-organizing maps, on a defect image database containing 2004 images from a Web inspection system. Six feature descriptors from the MPEG-7 standard and an additional shape descriptor developed for surface defect images are used in the experiments. The classification performance of the descriptors is evaluated using K-nearest neighbor (KNN) leave-one-out cross-validation and PicSOM´s built-in CBIR analysis system. The KNN results show good performance from three MPEG-7 descriptors and our shape descriptor. The CBIR results using these descriptors show that PicSOM´s SOM-based indexing engine yields efficient and accurate retrieval of similar defect images from our database.
Keywords :
Web sites; content-based retrieval; feature extraction; image retrieval; inspection; pattern classification; self-organising feature maps; visual databases; K-nearest neighbor; PicSOM; Web inspection system; Web surface defects; World Wide Web; content based image retrieval; defect image database; feature descriptors; self organizing maps; Content based retrieval; Image databases; Image retrieval; Information retrieval; Inspection; MPEG 7 Standard; Performance analysis; Self organizing feature maps; Shape; Standards development;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1380893