A Study of Image Engineering

A Study of Image Engineering

Yu-Jin Zhang (Tsinghua University, Beijing, China)
DOI: 10.4018/978-1-60566-026-4.ch575
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Abstract

Images are an important medium from which human beings observe the majority of the information they received from the real world. In its general sense, the word “image” could include all entities that can be visualized, such as a still image, video, animation, graphics, charts, drawings, even also text, and so forth. Nowadays, “image” rather than “picture” is used because computers store numerical images of a picture or scene. Image techniques, which are expanding over wider and wider application areas, have attracted more and more attention in recent years. Image engineering (IE), an integrated discipline/subject comprising the study of all the different branches of image techniques, is evolving quickly. From 1969 to 2000, a well-known bibliography series had been developed to offer a convenient compendium of the research in picture processing until 1986, as well as in image processing and computer vision after 1986. This series has been ended in 2000 by the author after a total of 30 survey papers were published (Rosenfeld, 2000a). Some limitations of this series for the termination are (Zhang, 2002b): 1. No attempt is made to summarize the cited references for each year. 2. No attempt is made to analyze the distributions of the selected references from various sources. 3. No attempt is made to provide statistics about the classified references in each group. Another survey series, but on IE, has been started since 1996 (Zhang, 1996a, 1996b, 1996c, 1997, 1998, 1999, 2000a, 2001a, 2002a, 2003, 2004, 2005). The purpose of this survey work is mainly to capture the up-to-date development of IE, to make available a convenient means of literature searching facility for readers working in related areas, and to supply a useful reference for the editors of journals and potential authors of papers. This new series overcame the weakness of the earlier mentioned one by summarizing the cited references for each year, analyzing the distributions of the selected references from various sources, and providing various statistics about the classified references in each group. This new survey series has already made consecutively for ten years. This article will present an overview of this survey series by showing the idea behind and consideration on this work as well as the comprehensive statistics obtained from this work.
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Introduction

Images are an important medium from which human beings observe the majority of the information they received from the real world. In its general sense, the word “image” could include all entities that can be visualized, such as a still image, video, animation, graphics, charts, drawings, even also text, and so forth. Nowadays, “image” rather than “picture” is used because computers store numerical images of a picture or scene. Image techniques, which are expanding over wider and wider application areas, have attracted more and more attention in recent years. Image engineering (IE), an integrated discipline/subject comprising the study of all the different branches of image techniques, is evolving quickly.

From 1969 to 2000, a well-known bibliography series had been developed to offer a convenient compendium of the research in picture processing until 1986, as well as in image processing and computer vision after 1986. This series has been ended in 2000 by the author after a total of 30 survey papers were published (Rosenfeld, 2000a). Some limitations of this series for the termination are (Zhang, 2002b):

  • 1.

    No attempt is made to summarize the cited references for each year.

  • 2.

    No attempt is made to analyze the distributions of the selected references from various sources.

  • 3.

    No attempt is made to provide statistics about the classified references in each group.

Another survey series, but on IE, has been started since 1996 (Zhang, 1996a, 1996b, 1996c, 1997, 1998, 1999, 2000a, 2001a, 2002a, 2003, 2004, 2005). The purpose of this survey work is mainly to capture the up-to-date development of IE, to make available a convenient means of literature searching facility for readers working in related areas, and to supply a useful reference for the editors of journals and potential authors of papers. This new series overcame the weakness of the earlier mentioned one by summarizing the cited references for each year, analyzing the distributions of the selected references from various sources, and providing various statistics about the classified references in each group. This new survey series has already made consecutively for ten years. This article will present an overview of this survey series by showing the idea behind and consideration on this work as well as the comprehensive statistics obtained from this work.

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Background

Image Engineering

IE, from a perspective more oriented to technique, could be referred to as the collection of three related and partially overlapped groups of image techniques, that is, image processing (IP), image analysis (IA), and image understanding (IU). In a structural sense, IP, IA, and IU build up three inter-connected layers of IE as shown in Figure 1. Each of them operates on different elements (IP’s operand is pixel, IA’s operand is object, and IU’s operand is symbol) and works with altered semantic levels (from low at IP to high at IU). The three layers follow a progression of increasing abstractness and of decreasing compactness from IP to IU.

Figure 1.

Three layers of image engineering

IP primarily includes the acquisition, representation, compression, enhancement, restoration, and reconstruction of images. While IP is concerned with the manipulation of an image to produce another (improved) image, IA is concerned with the extraction of information from an image. Compared to IP which takes an image as input and outputs also images, IA takes also an image as input but outputs data. Here, the extracted data can be the measurement results associated with specific image properties or the representative symbols of certain object attributes. Based on IA, IU refers to a body of knowledge used in transforming this extracted data into certain commonly understood descriptions and for making subsequent decisions and actions according to the interpretation of the images.

Key Terms in this Chapter

Image Segmentation: A process consists of subdividing an image into its constituent parts and extracting these parts of interest (objects) from the image.

Image: An entity that was captured by some visual systems in looking at the real world and that can be sensed to produce perception. It is a representation, likeness, or imitation of an object or thing, a vivid or graphic description, something introduced to represent something else.

Image Analysis: One of three layers of image engineering, which is concerned with the extraction of information (by meaningful measurements with descriptive parameters) from an image (especially from interesting objects).

Image Processing: One of three layers of image engineering, which encompasses processes whose inputs and outputs are both images, with the outputs being improved version of inputs.

Image Coding: A process for representing an image with some other representations in view of reducing data for storage and/or transmission of this image.

Image Engineering: An integrated discipline/subject comprising the study of all the different branches of image and video techniques.

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