| Summary: | 碩士 === 國立臺灣科技大學 === 資訊工程系 === 95 === Image annotation refers to the labeling of images with a set of predefined keywords that is mainly used for visual information management. Image annotation can be applied in a variety of domains such as biomedicine, military, web image classification, search, etc. Image annotation employs low-level features to distinguish image contents such as color, shape, texture, etc.
The Border/Interior pixel Classification (BIC) features [15] are very compact and efficient features that capture color, shape, and texture information. But the BIC features inherit the problem that the differences on utilization rates of each feature are high.
We propose to employ the Hilbert-Scan method and the Iterative Partitioning Method (IPM) to improve the utilization rates of each feature which results in higher accuracy for image annotation. Finally, we show that our proposed method is effective in annotating 6000 images in 60 categories.
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