Non-photographic Image Categorization
نویسنده
چکیده
The rapid growth of IT industry today has undoubtedly boosted the widespread use of computer images in both web pages and modern computer programs. Applications like online image search, automatic webpage summarization and web mining, rely heavily on image categorization. This project presents a system that categorizes non-photographic images 1 based on their textual and image features. The correlation between image category and each of these features is also examined. Some example categories defined in this project include map, diagram, icon, artwork and cartoon. With the machine learning program “BoosTexter” and a large set of training data obtained from Google, the system is able to correctly categorize images up to an accuracy of around 97.6%. Subject descriptors: I.2.6 Learning I.4.10 Image Representation I.5.2 Design Methodology
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تاریخ انتشار 2004