Iris recognition is a biometric modality which offers the potential for high accuracy and, increasingly, for application in more diverse environments than hitherto. Poor segmentation is one of the most important factors likely to compromise iris recognition performance. Hence, research in the area of iris biometrics has often been focused on efforts to enhance the performance of iris segmentation techniques, and this has led to considerable work on iris segmentation. This paper presents a detailed investigation, evaluation and comparison of several segmentation approaches (including a new algorithm proposed by the authors) proposed in the literature based on their accuracy and processing speed. To be consistent with the research of others, for all quantitative experiments, algorithms have been evaluated on two iris databases, namely CASIA V1.0 and a subset of the BioSecure database. (6 pages)