Single-layered Cloud Types

The paper presents an automatic classification system, which discriminates the diferent types of'siniglelayered clouds uising Principal Component Anialysis (PCA) with enhanced accuracy as compared to other techniques. PCA is an image classification techniqute typically used for ace recognition. Principal components are the distinctive or peculiar featuires of an image. The approach described in this paper iuses this PCA capability Jbr enhancing the accuracy of cloud image analysis. To demonstrate this enhancement, a soJtware classifier system has been developed that incorporates PCA capability Jbr better discrimination of clouid images. The system is first trained using clouid images. In training phase, system reads mqjor principal features of the different cloud images to produce an image space. In testing phase, a new cloud image can be classified by comparing it with the specified image space using the PCA algorithm.