TY - JOUR
T1 - Modified Fractal Signature (MFS)
T2 - a new approach to document analysis for automatic knowledge acquisition
AU - Tang, Yuan Y.
AU - Ma, Hong
AU - Xi, Dihua
AU - Mao, Xiaogang
AU - Suen, Ching Y.
N1 - Funding Information:
This work was supported by research grants received from the Research Grant Council (RGC) of Hong Kong and by a Faculty Research Grant (FRG) of Hong Kong Baptist University. This work was also supported by the Ministry of Education of the People’s Republic of China, and Sichuan University, China. We wish to express our gratitude to Professors Zhisheng You, Jiansun Nie, Hui Li, and other staff members at Sichuan University, China, for their assistance in this research project.
Publisher copyright:
© 1997 IEEE
PY - 1997/9
Y1 - 1997/9
N2 - One of the key technologies related to knowledge and data engineering is the acquisition of knowledge and data in the development and utilization of information system and the strategies to capture new knowledge and data. Actually, millions of documents, including technical reports, government files, newspapers, books, magazines, letters, bank checks, etc., have to be processed every day, and knowledge has to be acquired from them. This paper presents a new approach to document analysis for automatic knowledge acquisition. The traditional approaches have two major disadvantages: (1) They are not effective for processing documents with high geometrical complexity. Specially, the top-down approach can process only the simple documents which have specific format or contain some a priori information. (2) The top-down approach needs to split large components into small ones iteratively, while the bottom-up approach needs to merge small components into large ones iteratively. They are time consuming. This new approach is based on modified fractal signature. It can overcome the above weaknesses.
AB - One of the key technologies related to knowledge and data engineering is the acquisition of knowledge and data in the development and utilization of information system and the strategies to capture new knowledge and data. Actually, millions of documents, including technical reports, government files, newspapers, books, magazines, letters, bank checks, etc., have to be processed every day, and knowledge has to be acquired from them. This paper presents a new approach to document analysis for automatic knowledge acquisition. The traditional approaches have two major disadvantages: (1) They are not effective for processing documents with high geometrical complexity. Specially, the top-down approach can process only the simple documents which have specific format or contain some a priori information. (2) The top-down approach needs to split large components into small ones iteratively, while the bottom-up approach needs to merge small components into large ones iteratively. They are time consuming. This new approach is based on modified fractal signature. It can overcome the above weaknesses.
KW - δ-parallel bodies
KW - Automatic knowledge acquisition
KW - Blanket method
KW - Document analysis
KW - Minkowski dimension
KW - Modified fractal signature
UR - http://www.scopus.com/inward/record.url?scp=0031223651&partnerID=8YFLogxK
U2 - 10.1109/69.634753
DO - 10.1109/69.634753
M3 - Journal article
AN - SCOPUS:0031223651
SN - 1041-4347
VL - 9
SP - 747
EP - 762
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
IS - 5
ER -