A fuzzy rule base system for object-based feature extraction and classification

Xiaoying Jin; Scott Paswaters

doi:10.1117/12.720063

7 May 2007 A fuzzy rule base system for object-based feature extraction and classification

Xiaoying Jin, Scott Paswaters

Proceedings Volume 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI; 65671H (2007) https://doi.org/10.1117/12.720063
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

In this paper, we present a fuzzy rule base system for object-based feature extraction and classification on remote sensing imagery. First, the object primitives are generated from the segmentation step. Object primitives are defined as individual regions with a set of attributes computed on the regions. The attributes computed include spectral, texture and shape measurements. Crisp rules are very intuitive to the users. They are usually represented as "GT (greater than)", "LT (less than)" and "IB (In Between)" with numerical values. The features can be manually generated by querying on the attributes using these crisp rules and monitoring the resulting selected object primitives. However, the attributes of different features are usually overlapping. The information is inexact and not suitable for traditional digital on/off decisions. Here a fuzzy rule base system is built to better model the uncertainty inherent in the data and vague human knowledge. Rather than representing attributes in linguistic terms like "Small", "Medium", "Large", we proposed a new method for automatic fuzzification of the traditional crisp concepts "GT", "LT" and "IB". Two sets of membership functions are defined to model those concepts. One is based on the piecewise linear functions, the other is based on S-type membership functions. A novel concept "fuzzy tolerance" is proposed to control the degree of fuzziness of each rule. The experimental results on classification and extracting features such as water, buildings, trees, fields and urban areas have shown that this newly designed fuzzy rule base system is intuitive and allows users to easily generate fuzzy rules.

Citation Download Citation

Xiaoying Jin and Scott Paswaters "A fuzzy rule base system for object-based feature extraction and classification", Proc. SPIE 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI, 65671H (7 May 2007); https://doi.org/10.1117/12.720063

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