Imaging and Optics Technology in Modern Business Communication

Imaging and optic applications are truly ancient, and people quickly recognized the innovation these devices represented. "Two thousand years ago," Peter Weiss notes, "Roman Emperor Nero peered through an emerald monocle to better see his gladiators in combat. Twelve hundred or so years later, eyeglasses started to adorn faces" (p. 200). To date, optical lenses have primarily served one purpose: to provide the viewer with a more visible image of the world. Things are changing, however, and they are changing fast. "Now, there are inanimate observers that can also benefit from lenses," Weiss says, and "more and more, computers are being tasked with making sense of the visual world in ways that people can't" (p. 200).

According to Rudolf Kingslake and Brian J. Thompson (2005), "A new era in optics commenced in the early 1950s following the impact of certain branches of electrical engineering—most notably communication and information theory. This impetus was sustained by the development of the laser in the 1960s" (p. 5). The initial association between optics and communication theory emerged based on the wide range of similarities between the two subjects as well as the similar mathematical techniques used to formally describe the behavior of both electrical circuits and optical systems (Kingslake & Thompson, 2005). In the Digital Age, these considerations have assumed new levels of importance.

A topic of considerable concern since the invention of the lens as an optical imaging device has always been the description of the optical system that forms the image; information about the object is relayed and presented as an image. As Kingslake and Thompson explain, "the optical system can be considered a communication channel and can be analyzed as such. There is a linear relationship (i.e., direct proportionality) between the intensity distribution in the image plane and that existing in the object, when the object is illuminated with incoherent light (e.g., sunlight or light from a large thermal source)" (2005, p. 5). Consequently, the linear theory developed to describe new electronic systems can also be applied to optical image-forming systems. For instance, an electronic circuit can be characterized by its impulse response—that is, its output for a brief impulse input of current or voltage. Similarly, an optical system can be characterized by an impulse response that, for an incoherent imaging system, is the intensity distribution in the image of a point source of light. The primary difference is that the optical impulse is spatial rather than temporal; otherwise, the fundamental concept is identical (Kingslake & Thompson, 2005).

These are important considerations for industries seeking better ways to accomplish data processing and process management, because it means that computer-assisted technologies can be applied to once-limited optical devices. As Kingslake and Thompson point out, "Once the appropriate impulse response function is known, the output of that system for any object intensity distribution can be determined by a linear superposition of impulse responses suitably weighted by the value of the intensity at each point in the object. For a continuous object intensity distribution this sum becomes an integral" (2005, p. 6). Although this example concerns the use of an optical imaging system—by far the most common use of optical elements today—the concept can actually be applied independently of whether the receiving plane is an image plane or not. Therefore, an impulse response can be defined for an optical system that is deliberately defocused, or for systems used for the display of Fresnel or Fraunhofer diffraction patterns. The Fraunhofer diffraction takes place when the light source and diffraction patterns are effectively at infinite distances from the diffracting system; by contrast, Fresnel diffraction occurs when one or both of the distances are finite (Kingslake & Thompson, 2005).

In his essay "Pictures Only a Computer Could Love," Peter Weiss of Science News (2003) reports, "With a new generation of optics, engineers are recasting visual scenes for computers' consumption. To the human eye, these pictures are visual gibberish, hardly worth a single word, let alone a thousand. To computers, such data can be worth more words than you'd care to count" (p. 200). Underlying all of these innovations in digitally enhanced processing are improvements in new styles of lenses. Rather than employing the traditional concave and convex disks to develop images, optical engineers today are using oddly shaped, radically different lenses that are customized to take advantage of the strengths of computers. According to Joseph N. Mait of the Army Research Laboratory and the National Defense University in Washington, D.C., "Once you break away from thinking that the optics have to form something [people] recognize as an image, there are many things that you can do." Similarly, Eustace L. Dereniak points out that "There's no reason to go ahead and form an image" (in Weiss, 2003, p. 200).

Even in nature, there are some species of beetles able to navigate by detecting specific colors or by the polarization of light in space without forming a conventional image. To date, there has been a "human-centrist" tendency to avoid such techniques because humans have modeled optical instruments—such as cameras—after our own image-making eyeballs (Weiss, 2003). Innovations on the horizon also transcend optical phenomena altogether; researchers expect to be able to make lenses that process other segments of the electromagnetic spectrum. According to David J. Brady, "It's a general change in the way you think about sensing" (in Weiss, 2003, p. 201). Technologies that stand to benefit from these radical new approaches include radar, computerized axial tomography (CAT) X-ray scanners, and magnetic resonance imaging (MRI) systems. These and other current and emerging technologies that rely on imaging and optical scanning provide improved methods of personal identification, better security, and the elimination of human errors compared with past methods.

More and more industries today are enjoying the benefits of improved imaging and optical scanning techniques. These advantages extend to improved inventory management and warehousing requirements, improved supply chains, better security, and—increasingly—real-time tracking of inventory as it moves through entire production, marketing, and delivery systems. These technologies also allow for automated identification and verification of individuals, a topic that is receiving increasing attention in a world characterized by unexpected acts of terrorism. Furthermore, these technologies are providing companies in almost every industry with an improved ability to manage information, something that has assumed new levels of importance in the Age of Information.

The term "automatic identification" refers to "a means of identifying a product mechanically and entering the data obtained automatically into a computer" (A Dictionary of Business, 1996, p. 40). The most common applications of automatic identification include bar codes, optical character recognition (OCR), magnetic ink character recognition (MICR), magnetic stripes, and voice systems (A Dictionary of Business, 1996). The ability of companies to automatically identify components and finished goods as they move through the supply chain has assumed increasing importance in a globalized marketplace.

Data capture applications have also been extended to global mapping systems that have revolutionized consumer products by adding global positioning systems (GPS) originally developed for military purposes (Bildirici, 2004). According to Bildirici, "Computer technology has been widely used in cartography since the 1970s. New technologies have led to a rapid development in the field of data capture in cartography and related disciplines. In developed countries in particular, the era of data capture is almost complete" (p. 43). Such automated techniques also helped the U.S. Census Bureau perform a wide range of functions for Census 2000, including data collection and data capture activities (Longini, Marshall, Palensky et al., 2002). In terms of navigation, a longer-term technology could involve electronic fixed-response transponders scanned via antennas embedded in the pavement, thereby providing obstruction-free scanning (Bowman, Hakim & Seidenstat, 1996).

Character Recognition

By the beginning of the 1980s, various optical character recognition (OCR) technologies became available that made it possible to convert text to electronic form without manual keyboarding (Dry & Lawler, 1998). A scanner's ability to translate typewriter characters from a bit-mapped image into ASCII text depends on a number of factors, including the sensitivity of the device and the legibility and preparation method of the original document. Improvements are being made continually, and even formerly graphic-based scanning systems such as Adobe's PDF applications have incorporated character recognition systems that allow for textual scanning. Some of these systems incorporate features that provide output options to convert text into formats used by common word-processing programs such as RTF and Word.

According to Dry and Lawler, the term "scanning" is frequently used today to describe the process of creating digitized images; in this approach, a graphic picture of the page, rather than an actual transcription of the text itself, is stored in the computer. "While this provides an effective means of delivering text for reading, the text itself in such an image cannot be processed in any way by the computer" (Dry & Lawler, p. 106).