Scanning software is used with optical and document scanners or with other imaging equipment to digitize, create, edit and evaluate images. Document scanners are devices that scan two-dimensional (2D) objects and convert them into digital images. Optical scanners use rows of light receptors to detect variations in light. These rows of receptors are arrayed into a charge-coupled device (CCD), and vary in quality from one optical scanner to the next. For both document scanners and optical scanners, scanning software is used to create, digitize, and modify images for storage on personal computers (PCs), compact discs (CDs), electronic document management (EDM) systems, and other electronic media.
Selecting Scanning Software
Selecting scanning software requires an analysis of product types, specifications, features, and applications. Scanning software is designed for use with specific types of image scanners. Examples include drum scanners and flatbed scanners. Drum scanners use upon photomultiplier tubes (PMT) instead a charged coupled device (CCD) or charge injection system (CIS).
Operators place the object to be scanned upon a large, glass drum with an acrylic cylinder that rotates at high speeds. The ability to control aperture and sample-size make drum scanners a good choice for applications that require the enlargement of originals. Unlike drum scanners, flatbed scanners use CCDs and a flat glass pane called a platen. A xenon or cold cathode fluorescent light is used to illuminate the pane. Color flatbed scanners are image scanners with separate sensor arrays with red, green, and blue filters. Scanning software for other types of image scanners is also available.
Product specifications for scanning software include image recognition accuracy, page layout reconstruction accuracy, support for languages, speed, and operating system (OS). Support for searchable outputs and the quality of the user interface are also important considerations. Some scanning software and scanning systems are capable of reproducing formatted outputs that closely approximate the original document, even in terms of images, columns, and other non-textual components. Pattern recognition, artificial intelligence, and machine vision are used to convert scanned images into files that are then added to searchable databases. Such scanning software allows the retrieval of scanned images based upon their content.