The eye has often been thought of as the window into the human soul, and the iris—the ring of colored fibrous tissue controlling the aperture (pupil) at the front of the eye—seen as an external indicator of one’s hidden depths.
Since ancient Egyptian times, observation of human iris patterns has been used to divine all kinds of things, persisting today in the “new age” practice of iridology. However, the path that led to today’s biometric iris recognition started with Frenchman Alphonse Bertillon, often dubbed the father of forensic science. Dissatisfied with ad hoc methods then used to identify criminals, he set about researching a whole system of anthropometric measurements. Amongst other things, in 1893 he reported on nuances he found in the human iris. Much of his other work also bears on present human biometric identification techniques.
Later in 1949, observations about human iris variation were published by British ophthalmologist J.H. Doggart, and referred to in a 1953 textbook Physiology of the Human Eye (still the basis of current ophthalmic study). In the text, F.H. Adler, a German scientist, wrote: "In fact, the markings of the iris are so distinctive that it has been proposed to use photographs as a means of identification, instead of fingerprints."
In fact, the fibrous texture of the human iris develops randomly in the womb, and is stable within a few months after birth. It’s this high degree of randomness that gives iris recognition its potential discrimination power. While its color is genetically determined, its structure is not.
This was picked up by two American ophthalmologists, Leonard Flom and Arun Safir, who in 1986 managed to patent the concept of using a digital image of the eye as a human identifier. The first algorithms were developed in the early 1990s by John Daugman, a computer scientist at the University of Cambridge.
Today’s Iris Biometric Technology
Fast forward to the current decade, and many companies now offer iris biometric products. FotoNation owns and offers MIRLIN technology, based on algorithms originally developed by Smart Sensors Limited. It’s used on products like Northrop Grumman’s BioSled multimodal, biometric capture device (see figure).