Ricardo Carmona Galán

Institute of Microelectronics of Seville

Bio

R. Carmona-Galán (M'04) graduated in physics and received the Ph.D. degree in microelectronics from the University of Seville, Seville, Spain, in 1993 and 2002, respectively.

He started research activities in analog and mixed-signal integrated circuit design as an undergraduate student at the National Center for Microelectronics (CSIC), Seville, Spain. From 1994 to 1996, he was funded by Iberdrola S.A. From July 1996 to June 1998, he worked as a Research Assistant at Prof. Chua's laboratory in the Electrical Engineering and Computer Science Department of the University of California, Berkeley. From 1999 to 2005, he was an Assistant Professor of the Department of Electronics of the University of Seville. He taught circuit analysis and synthesis at the School of Engineering. Since 2005, he has been a Tenured Scientist at the Institute of Microelectronics of Seville (IMSE-CNM-CSIC). His main research focus has been on VLSI implementation of concurrent sensor/processor arrays for real-time image processing and vision. He also held a PostDoc at the University of Notre Dame, Notre Dame, IN (2006–2007), where he worked in interfaces for CMOS-compatible nanostructures for multispectral light sensing. He has collaborated with start-up companies in Seville (AnaFocus) and Berkeley (Eutecus). He has designed several vision chips implementing different focalplane operators for early vision processing. His current research interests lie in the design of low-power smart image sensors and 3-D integrated circuits for autonomous vision systems. He has authored more than 60 papers in refereed journals and conferences and several book chapters.

Dr. Carmona-Galán received a Best Paper Award in 1999 from the International Journal of Circuit Theory and Applications. He is a co-recipient of an award of the ACET in 2002 and a Certificate of Teaching Excellence from the University of Seville. 

Abstract

Efficient Feature Extraction in CMOS Vision Sensors

Out of the enormous data flow conveyed by the visual stimulus, only a small fraction contains relevant information. In the conventional image processing chain, all the pixel values are converted to digitalpriorto any operation. This can be a waste of time and energy. Biological vision systems  are known to extract distinctive features from the image before trying to analyze the objects in the scene and their interactions. CMOS technology provides the opportunity to incorporate processing close to the photosensor array. By using a hierarchical architecture with distributed processing and memory resources, built with relatively coarse analog and mixed-signal circuits, efficient on-chip implementation of feature extraction is possible.