Introduction Directory UMM :Data Elmu:jurnal:B:Biosystems:Vol54.Issue3.2000:

BioSystems 54 2000 131 – 140 Color sensitive retina based on bacteriorhodopsin Michael Frydrych a , Pertti Silfsten b , Sinikka Parkkinen c , Jussi Parkkinen d, , Timo Jaaskelainen e a Department of Information Technology, Lappeenranta Uni6ersity of Technology, Lappeenranta, Finland b Department of Electrical Engineering, Lappeenranta Uni6ersity of Technology, Lappeenranta, Finland c Department of Biology, Uni6ersity of Joensuu, Joensuu, Finland d Department of Computer Science, Uni6ersity of Joensuu, PO Box 111 , 80101 Joensuu, Finland e Va¨isa¨a¨la¨ Laboratory, Uni6ersity of Joensuu, Joensuu, Finland Received 5 January 1999; received in revised form 8 October 1999; accepted 15 October 1999 Abstract Bacteriorhodopsin BR, a membrane protein of a microorganism Halobacterium salinarium has been studied since the 80’s as a potential material for information technology. The information processing applications of BR employ either photochromic or photoelectric properties of the protein. In this study we discuss about design principles and describe our study of the use of bacteriorhodopsin as a sensor material for a color sensitive artificial retina. This retina includes low-level processing of input information. The design of a color sensitive matrix element, the self-organizing color adaptation algorithm and a system model for the retina are presented. © 2000 Elsevier Science Ireland Ltd. All rights reserved. Keywords : Artificial retina; Bacteriorhodopsin; Color space; Color sensor; Vision system www.elsevier.comlocatebiosystems

1. Introduction

Although all parts of the eye are important for perceiving a good image, the most vital one is the retina. The retina is a part of a brain tissue, which directly interacts with the light and images of the outside. It is the only part of the brain that is visible from outside the skull. The retina contains photoreceptors and five layered neural structure, which is claimed to have some capability of sim- ple processing of visual information Dowling, 1987. Even a simple two-layer neural network is capable of low level image processing Mantere et al., 1992. The whole human visual system includes also the lateral geniculate nucleus, ‘a relay station’ in the thalamus and the visual cortex. Actually, the image is processed not only on one cortical re- gion, but on a network of over 20 cortical areas Kosslyn, 1996. The exact meaning of each com- ponent for visual processing is not known, but certain low level processing is done in the retina and a high level conceptual processing in the cortical areas Zeki, 1993. Like other neural or- Corresponding author. Tel.: + 358-13-2513106; fax: + 358-13-2513290. E-mail address : jussi.parkkinencs.joensuu.fi J. Parkkinen 0303-264700 - see front matter © 2000 Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 3 0 3 - 2 6 4 7 9 9 0 0 0 7 4 - X ganism, the visual system is modified through learning, mainly during early years of infancy Teller, 1997. An important attribute of human visual system is color. The sense of color originates from re- sponses of three types of color sensitive photore- ceptors in the retina, cones, to a spectrum of electromagnetic radiation originated from an ob- ject observed Wandell, 1995. Several distinct codings of color exist in the visual system. The triplets of cone responses can be regarded as the initial one. The receptor responses are trans- formed into achromatic and color-opponent sig- nals Buchsbaum and Gottschalk, 1983. This transformation occurs in the retina and is retained until the early cortical areas. These broadband signals are afterwards transformed to narrow- band responses of cells at the higher cortical areas, namely area V4 De Valois and De Valois, 1993; Kosslyn, 1996. The human visual system has been a common source of inspiration in machine vision research Marr, 1982; Jain, 1989. For more than the last 10 years, many sensors, which include both the photosensors and parallel processing elements have been reported. Mainly these are silicon based special circuits, often called vision chips, smart sensors or artificial retinas Moini, 1997. There are also some constructions of bacteriorhodopsin- based detectors Miyasaka et al., 1992; Chen and Birge, 1993; Martin et al., 1997. These detectors use a photoelectric property of bacteriorhodopsin BR. Miyasaka et al. 1992 constructed BR- based detector in a matrix form. They have immo- bilized BR on a silicon circuit by the Langmuir – Blodgett method, forming a matrix of size 8 × 8 pixels. They used S-9 strain of Halobac- terium salinarium with the maximum photocurrent at the wavelength 560 nm, with the width at half maximum being about 100 nm. Therefore, it can be used as a monochromatic detector. We have developed a model for a color sensi- tive artificial retina, in which photosensitive ele- ments are based on BR. This retina includes low-level processing of input information. The processing consist in color space transformation. In order for the retina to operate in similar fash- ion as the natural system does, we employ an artificial neural network learning algorithm, to tune color space transformation parameters for the environment in which the retina operates. In this report, we present the design of a color sensitive matrix element, the learning algorithm and the system model for the color sensitive, protein based, artificial retina.

2. Bacteriorhodopsin