A ground-based real-time remote sensing system for detecting diseases in arable crops under field conditions is developed by Moshou, (2005), which considers the early stage of disease development. The authors have used hyper-spectral reflection images of infected and healthy plants with an imaging spectrograph under ambient lighting conditions and field circumstances. They have also used multi-spectral fluorescence images simultaneously using UV-blue excitation on the same plants. They have shown that it is possible to detect presence of disease through the comparison of the 550 and 690 nm fluorescence images. Color based features are also used by Singh et al. (2012) and clustering is also performed for human activity recognition (Gupta et al., 2013).