linear median, order statistics, homomorphic, a-trimmed median, generalized mean, nonlinear mean and fuzzy nonlinear filters. New versions of polynomial filters, such as quadratic filters, were also studied by Professor Venetsanopoulos. He designed new morphological filters, which lead to various detection and recognition applications. Finally, he conducted extensive research in the area of Adaptive filters. Professor Venetsanopoulos developed Adaptive Order Statistics filters, Adaptive LMS/RLS filters, Adaptive L-filters and Adaptive morphological filter algorithms. These filters are extensively used in numerous biomedical applications, such as in radiology, mammography and tomography. Among other applications, they are also applied to financial data processing and remote sensing. In the nineties, Professor Venetsanopoulos contributed to the field of color image processing and analysis, where he introduced a number of techniques for color image enhancement filtering and analysis. He also introduced the so-called vector directional filter family, which operates along the direction of the color vectors. A new class of adaptive nonlinear filters was developed. Fuzzy membership functions based on different distance measures were adopted to determine the weights of new nonlinear, adaptive filters. The new filters encompassed different classes of existing nonlinear filters as special cases. For the first time, the color image was treated as a vector field and edge information carried directly by the color vectors was exploited using vector order statistics. Multimedia signal processing In 1999 Professor Venetsanopoulos became the Inaugural Chair of the Bell Canada Multimedia Systems Laboratory at the University of Toronto. From that year, he contributed to the area of multimedia data mining and information retrieval by addressing two key technical challenges: a) the problem of similarity determination within the visual data domain, b) the interactive learning of user intentions and automatic adjustment of system parameters for improved retrieval accuracy. He developed still image and video retrieval systems that utilized color content queries. The system implemented a new vector-based approach to image retrieval using an angular-based similarity measure. The scheme he developed addresses the drawbacks of the histogram techniques, it is flexible, and outperforms established retrieval systems. He also developed an interactive learning algorithm for resolving ambiguities arising due to the mismatch between machine-representation of images and human context-dependent interpretation of visual content. His proposed solution exploited feedback from users during retrieval sessions, to adapt their query intentions and improve the accuracy of the retrieved results. Biometrics research For thousands of years, humans have used visually-perceived body characteristics such as face