Stripe: Image feature based on a new grid method and its application in ImageCLEF

Qiu Bo, Daniel Racoceanu, Sheng Xu Chang, Tian Qi

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There have been many features developed for images, like Blob, image patches, Gabor filters, etc. But generally the calculation cost is too high. When facing a large image database, their responding speed can hardly satisfy users' demand in real time, especially for online users. So we developed a new image feature based on a new region division method of images, and named it as 'stripe'. As proved by the applications in ImageCLEF's medical subtasks, stripe is much faster at the calculation speed compared with other features. And its influence to the system performance is also interesting: a little higher than the best result in ImageCLEF 2004 medical retrieval task (Mean Average Precision - MAP: 44.95% vs. 44.69%), which uses Gabor filters; and much better than Blob and low-resolution map in ImageCLEF 2006 medical annotation task (classification correctness rate: 75.5% vs. 58.5% & 75.1%).

Idioma originalInglés
Título de la publicación alojadaInformation Retrieval Technology - Third Asia Information Retrieval Symposium, AIRS 2006, Proceedings
EditorialSpringer Verlag
Número de páginas8
ISBN (versión impresa)3540457801, 9783540457800
EstadoPublicada - 2006
Publicado de forma externa
Evento3rd Asia Information Retrieval Symposium, AIRS 2006 - Singapore, Singapur
Duración: 16 oct. 200618 oct. 2006

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4182 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349


Conferencia3rd Asia Information Retrieval Symposium, AIRS 2006


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