Registration of thermal and visible light images of diseased plants using silhouette extraction in the wavelet domain. Issue 7 (July 2015)

• Record Type: Journal Article
• Authors: Raza, Shan-e-Ahmed; Sanchez, Victor; Prince, Gillian; Clarkson, John P.; Rajpoot, Nasir M.
• Is Part Of: Pattern recognition. Volume 48:Issue 7(2015:Jul.)
• Page Start: 2119
• Page End: 2128
• Publication Date: 2015-07
• Subjects: Thermal and visible image registration -- Silhouette extraction -- Stationary wavelet transform -- Infrared imaging; Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2015.01.027
• Languages: English
• ISSNs: 0031-3203

Abstract

Abstract: The joint analysis of thermal and visible light images of plants can help to increase the accuracy of early disease detection. Registration of thermal and visible light images is an important pre-processing operation to perform this joint analysis correctly. In the case of diseased plants, registration using common methods based on mutual information is particularly challenging since the plant texture in the thermal image significantly differs from the corresponding texture in the visible light image. Registration methods based on silhouette extraction are therefore more appropriate. This paper proposes an algorithm for registration of thermal and visible light images of diseased plants based on silhouette extraction. The algorithm is based on a novel multi-scale method that employs the stationary wavelet transform to extract the silhouette of diseased plants in thermal images, in which common gradient-based methods usually fail due to the high noise content. Experimental results show that silhouettes extracted using this method can be used to register thermal and visible light images with high accuracy. Abstract : Highlights: Silhouette-based registration of thermal/visible light images of diseased plants. Novel silhouette extraction method based on stationary wavelet transform – SWT. High accuracy of SWT-based method compared to ground truth silhouettes. High accuracy of silhouette-based registration on several diseased plant images.