Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.creator | Huang, Xudong | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/5012 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | A system for document image classification | en_US |
| dcterms.abstract | In this thesis, the system for Document Image Classification is discussed in detail with three parts, i.e., document segmentation, and block classification and document classification. In fact, only document segmentation and document classification is used. The block classification does not need. The reason for it has been analyzed clearly. For the segmentation, the Fuzzy Segmentation Method (FSM) for the analysis of document images is developed. Based on the uses of the fuzzy set theory, the fuzzy blank and fuzzy black blocks are defined. The idea of 弇-cut sets is utilized when determining the vertical and horizontal thresholds in the segmentation process. With the definition of fuzzy sets, such a process can be made automatically in an adaptive manner. For the block classification, a system for automated pattern analysis and classification (APACS) method is applied to the block classification. The algorithm, features, and selection of the samples for using this method are specified. Furthermore, the part of affirming the feature of the blocks is omitted. The document classification algorithm in the third part employs the features of each block as parameters. This can reduce the error of recognition. The results are very satisfied. For the document classification, the Branch-and-Bound Technique is adopted to match two Attributed Random Graphs (ARGs) of a document. A new evaluation function of the Branch-and-Bound algorithm is proposed. ARG construction, decision tree construction and using branch-and-bound to match two ARGs are elaborated in detail. The document classification is successfully transferred to how to match the two ARGs. The experimental results are quite satisfied. | en_US |
| dcterms.extent | v, 73, [65] leaves : ill. ; 31 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2000 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Phil. | en_US |
| dcterms.LCSH | Document imaging systems | en_US |
| dcterms.LCSH | Pattern perception | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | open access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b15320534.pdf | For All Users | 4.52 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/5012