Statistics on Image Engineering Literatures

Statistics on Image Engineering Literatures

Yu-Jin Zhang (Department of Electronic Engineering, Tsinghua University, China)
Copyright: © 2015 |Pages: 11
DOI: 10.4018/978-1-4666-5888-2.ch595
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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 by human eyes, such as a still image or picture, a clip of video, as well as graphics, animations, cartoons, charts, drawings, paintings, even also text, etc. Nowadays, with the progress of information science and society, “image” rather than “picture” is used because computers store numerical images of a picture or scene.

Image techniques are those techniques that have been invented, designed, developed, implemented and used to treat various types of images for different and specified purposes (Zhang, 2009b). They are expanding over wider and wider application areas. They have attracted more and more attention in recent years with the fast advances of mathematic theories and physical principles, as well as the progress of computer and electronic devices, etc. Image engineering (IE), an integrated discipline/subject comprising the study of all the different branches of image techniques, which has been formally proposed and defined around 20 years ago (Zhang 1996a; Zhang 1996c) to cover the whole domain, is evolving quickly.

In the history, a well-known bibliography series to some related image techniques had been developed to offer a convenient compendium of the research in picture processing from 1969 till 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, 2000). Some limitations of this series are (Zhang, 2002b):

  • 1.

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

  • 2.

    No attempt was made to analysis the distributions of the selected references from various sources.

  • 3.

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

Another survey series, but on IE (with more wider coverage in the contents), have been started since 1996 and have been made already for consecutive 18 years (Zhang, 1996a; Zhang, 1996b; Zhang, 1997; Zhang, 1998; Zhang, 1999; Zhang, 2000a; Zhang, 2001; Zhang, 2002a; Zhang, 2003; Zhang, 2004; Zhang, 2005; Zhang, 2006; Zhang, 2007; Zhang, 2008a; Zhang, 2009a; Zhang, 2010; Zhang, 2011a; Zhang, 2012, Zhang, 2013). The summaries for several stages of this survey series can be found in (Zhang, 2000b; Zhang, 2002b; Zhang 2002c; Zhang 2008b; Zhang 2011b).

The main purpose of this survey work is triple, that is, 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 overcome the weakness of the above-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 subject group. This new survey series has already made consecutively for eighteen years. This chapter will present an overview of this survey series by showing the ideas behind and consideration on this work, as well as the comprehensive statistics obtained from this work. Some insights from it are also discussed.

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Background

For image engineering, a new discipline, the scope and related subjects are first described.

Key Terms in this Chapter

Image Understanding (IU): One of three layers of image engineering, which transforms data extracted from images into certain commonly understood descriptions, and makes subsequent decisions and actions according to the interpretation of the images.

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 (IA): 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 Engineering (IE): An integrated discipline/subject comprising the study of all the different branches of image and video techniques. As a general term for all image techniques, it could be considered as a broad subject encompassing mathematics, physics, biology, physiology, psychology, electrical engineering, computer science, automation, etc. Its advances are also closely related to the development of telecommunications, biomedical engineering, remote sensing, document processing, industrial applications, etc.

Image Techniques: A collection of various branches of techniques for processing (such as acquiring, capturing, sensing, storing, enhancing, filtering, debluring, inpainting, transforming, coding, transmitting, manipulating, etc .) analyzing (such as segmenting, representing, describing, featuring, measuring, classifying, recognizing), and understanding (such as modeling, registrating, matching, reconstructing, training, learning, reasoning, interpreting, etc .) images.

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