Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
AMORE: A World Wide Web image retrieval engine
World Wide Web
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Combining Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Bipartite graph reinforcement model for web image annotation
Proceedings of the 15th international conference on Multimedia
Effective term weighting in ALT text prediction for web image retrieval
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Image classification for content-based indexing
IEEE Transactions on Image Processing
A Study of Quality Issues for Image Auto-Annotation With the Corel Dataset
IEEE Transactions on Circuits and Systems for Video Technology
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The number of images on the World Wide Web has been increasing tremendously. Providing search services for images on the web has been an active research area. Web images are often surrounded by different associated texts like ALT text, surrounding text, image filename, html page title etc. Many popular internet search engines make use of these associated texts while indexing images and give higher importance to the terms present in ALT text. But, a recent study has shown that around half of the images on the web have no ALT text. So, predicting the ALT text of an image in a web page would be of great use in web image retrieval. We propose an approach on top of term co-occurrence approach proposed in the literature to ALT text prediction. Our results show that our approach and the simple term co-occurrence approach produce almost the same results. We analyze both the methods and describe the usage of the methods in different situations. We build an image annotation system on top of our proposed approach and compare the results with the image annotation system built on top of the term co-occurrence approach. Preliminary experiments on a set of 1000 images show that our proposed approach performs well over the simple term co-occurrence approach for web image annotation.