Automatic feature design for optical character recognition using an evolutionary search procedure

An automatic evolutionary search is applied to the problem of feature extraction in an OCR application. A performance measure based on feature independence is used to generate features which do not appear to suffer from peaking effects [17]. Features are extracted from a training set of 30 600 machine printed 34 class alphanumeric characters derived from British mail. Classification results on the training set and a test set of 10 200 characters are reported for an increasing number of features. A 1.01 percent forced decision error rate is obtained on the test data using 316 features. The hardware implementation should be cheap and fast to operate. The performance compares favorably with current low cost OCR page readers.     

Rule-based interpretation of aerial imagery

In this paper, we describe the organization of a rule-based system, SPAM, that uses map and domain-specific knowledge to interpret airport scenes. This research investigates the use of a rule-based system for the control of image processing and interpretation of results with respect to a world model, as well as the representation of the world model within an image/map database. We present results on the interpretation of a high-resolution airport scene wvhere the image segmentation has been performed by a human, and by a region-based image segmentation program. The results of the system's analysis is characterized by the labeling of individual regions in the image and the collection of these regions into consistent interpretations of the major components of an airport model. These interpretations are ranked on the basis of their overall spatial and structural consistency. Some evaluations based on the results from three evolutionary versions of SPAM are presented.     

Transformation between continuous and discrete representations of images: a perceptual approach

The transformation of image signals between the continuous domain of the real world and the discrete domain of modern data processing can have a significant effect on quality and efficiency. Analysis based on perceptual rather than mathematical considerations has been carried out. A series of experiments based on the analysis has shown that substantial improvement over usual techniques can be achieved by the use of a cascade of a presharpening filter combined with Gaussian presampling and interpolation filters. The resulting ``sharpened Gaussian' filter, although not exactly circularly symmetrical, gives a high degree of isotropy. Each element in the cascade is separable, so that computational efficiency is high. A favorable tradeoff is achieved among sharpness, smoothness, and the effects of aliasing. Subjective testing, in comparison with other commonly used filters, has shown the clear superiority of this filter.     

BPL: A set-based language for distributed system prototyping

Rapid prototyping of software and hardware is recognized as a very important step in timely, cost-effective system development. The complexity inherent in designing distributed computing systems and distributed problem solutions emphasizes the need for effective rapid prototyping tools. ADL/ADS is a testbed user interface tool for experimentation with critical research and design issues pertaining to distributed data processing (DDP). The experimenter expresses a candidate distributed system in terms of experiment objects, along with attributes and relationships. The experiment objects represent hardware, software, and behavior. This paper provides a brief overview of ADL/ADS, and gives especial emphasis to the Behavior Prototyping Language (BPL) within ADL/ADS. BPL is designed for expressing Behavior Modules (B_MODULEs)—the most versatile of the behavior objects. BPL incorporates set-theoretical approaches, and provides syntax designed for effectively describing manipulations of experiment objects, and their attributes and relationships.