The penetration and acceptance of Renewable Energy Systems (RESs) has already taken place in our lives. Solar energy is the feed-stock/source for various applications of RES, and thus, the knowledge of the intensity of the incident solar irradiance is essential for monitoring the performance of such systems. A lot of experimental work and modeling has already been conducted for calculating solar irradiance due to various factors, such as location and season. The major unpredictable factor in defining the solar irradiance and the performance of solar systems is the presence of clouds in the sky. So far, various researchers proposed several models for estimating solar irradiance in correlation with cloud coverage and cloud type. This paper reviews the up-to-date research in automatic cloud detection and classification. It initiates with a brief introduction to clouds types and classification. Then, a detailed description of the equipment used for the measurements is provided, either ground based or satellite integrated. Finally, it concludes with an analysis of the existing algorithms for cloud classification, including a presentation of the up-to-date experimental results. (C) 2012 Elsevier Ltd. All rights reserved.