In many areas of commerce, medicine, entertainment, education, weather forecasting the need for efficient image retrieval system has grown dramatically. Therefore, many researches have been done in this scope; however, researchers try to improve the precision and performance of such system. In this paper, we present an image retrieval method, which uses color and texture based approaches for feature extraction, fuzzy adaptive model and fuzzy integral. The system extracts color and texture features from an image and enhancing the retrieval by providing a unique adaptive fuzzy system that use fuzzy membership functions to find the region of interest in an image. The proposed method aggregates the features by assigning fuzzy measures and combines them with the help of fuzzy integral. Experimental results showed that proposed method has some advantages and better results versus related ones in most of the time.
Paper
Full text
A Novel Adaptive Fuzzy Model for Image Retrieval
Semantic Scholar · Computer Science · 2013
Abstract
In many areas of commerce, medicine, entertainment, education, weather forecasting the need for efficient image retrieval system has grown dramatically. Therefore, many researches have been done in this scope; however, researchers try to improve the precision and performance of such system. In this paper, we present an image retrieval method, which uses color and texture based approaches for feature extraction, fuzzy adaptive model and fuzzy integral. The system extracts color and texture features from an image and enhancing the retrieval by providing a unique adaptive fuzzy system that use fuzzy membership functions to find the region of interest in an image. The proposed method aggregates the features by assigning fuzzy measures and combines them with the help of fuzzy integral. Experimental results showed that proposed method has some advantages and better results versus related ones in most of the time.