WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 8, 2012
Fusion of Infrared and Visual Images Using Bacterial Foraging Strategy
Authors: ,
Abstract: This paper presents new methods for fusion of the visual and thermal images for pattern recognition. Researchers have suggested different fusion schemes to find out pattern vectors for object detection and recognition. The different fusion schemes are — data fusion, decision fusion etc. These schemes have been proposed in different way to improve the performance. Hence, here we propose three new methods for fusing the visual and infrared (IR) images. The proposed new methods are – fusion using information content from Gray Level Co-occurrence Matrix (GLCM), fusion using wavelet energy signature and fusion by maximizing wavelet energy signature using E. coli bacteria foraging strategy (EBFS). In the third method, we consider information fusion as an optimization problem and then solve it using EBFS as a search algorithm. Finally, we compare the results using the contrast signature from GLCM and observed that the later scheme using EBFS shows better results than other two methods.