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Creating a Large-Scale Content-Based Airphoto Image Digital Library (2000)
| Content Provider | CiteSeerX |
|---|---|
| Author | Zhu, Bin Ramsey, Marshall Chen, Hsinchun |
| Abstract | This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. The major contributions of this paper are two. 1) We suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement, and image compression, as well as information analysis technique such as self-organizing map (SOM) into an effective large-scale geographical image retrieval system. 2) We present two experiments that evaluate the performance of the Gaborfilter -extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model. |
| File Format | |
| Volume Number | 9 |
| Journal | IEEE TRANSACTIONS ON IMAGE PROCESSING |
| Language | English |
| Publisher Date | 2000-01-01 |
| Access Restriction | Open |
| Subject Keyword | Self-organizing Map Human Perception Image Enhancement Image Representation Algorithm Prototype System Geographical Image Retrieval Content-based Image Retrieval Digital Library Gabor Filter Human Mental Model Major Contribution Corresponding Similarity Measure Aerial Photograph Image Categorization Method Information Analysis Technique Image Compression Various Image Processing Technique |
| Content Type | Text |
| Resource Type | Article |
