Image Processing and Recognition

Abstract

The chapter presents the basic techniques used for image processing and pictorial pattern recognition by digital computer. One of the principal goals of image processing is to improve the appearance of the picture by increasing contrast, reducing blur, or removing noise. Methods of doing this are image enhancement or image restoration. Many image processing techniques involve advanced mathematical concepts. The chapter reveals that both image processing and analysis have pictures as input, in the form of arrays of gray levels. This chapter explains a selection of the ideas and methods used in digital image processing and analysis. The chapter provides a nontechnical introduction to some of the basic techniques. Digital image processing and recognition techniques have a broad variety of applications. Image coding is used extensively to reduce the time or bandwidth required for image transmission. Image enhancement and restoration techniques are very helpful in improving the usefulness of images taken near the limits of resolution or under adverse conditions. Pictorial pattern recognition has innumerable applications in document processing such as character recognition; industrial automation such as inspection, and vision-controlled robot assembly; medicine such as hematology, cytology, radiology, and remote sensing, to name only a few of the major areas. The chapter concludes that many of these applications have led to the development of commercial image processing and recognition systems.