Abstract
This paper presents a novel method of automatic image semantic annotation. Our approach is based on the Image-Keyword Document Model (IKDM) with image features discretization. According to IKDM, the image keyword annotation is conducted using image similarity measurement based on language model from text information retrieval domain. Through the experiments on a testing set of 5000 annotated images, our approach demonstrates great improvement of annotation performance compared with the known discretization-based image annotation model such as CMRM. Our approach also performs better in annotation time compared with the continuous model such as CRM.
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Zhou, X., Chen, L., Ye, J., Zhang, Q., Shi, B. (2005). Automatic Image Semantic Annotation Based on Image-Keyword Document Model. In: Leow, WK., Lew, M.S., Chua, TS., Ma, WY., Chaisorn, L., Bakker, E.M. (eds) Image and Video Retrieval. CIVR 2005. Lecture Notes in Computer Science, vol 3568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526346_22
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DOI: https://doi.org/10.1007/11526346_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27858-0
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