Shengrong Gong - Advanced Image and Video Processing Using MATLAB

Editorial Board

Li Cheng, The Hong Kong Polytechnic University, Hong Kong

Jeng-Haur Horng, National Formosa University, Yulin, Taiwan

Pedro U. Lima, Institute for Systems and Robotics, Lisbon, Portugal

Mun-Kew Leong, Institute of Systems Science, National University of Singapore

Muhammad Nur, Diponegoro University, Semarang, Indonesia

Luca Oneto, University of Genoa, Italy

Kay Chen Tan, National University of Singapore, Singapore

Sarma Yadavalli, University of Pretoria, South Africa

Yeon-Mo Yang, Kumoh National Institute of Technology, Gumi, South Korea

Liangchi Zhang, The University of New South Wales, Australia

Baojiang Zhong, Soochow University, Suzhou, China

Ahmed Zobaa, Brunel University, Uxbridge, Middlesex, UK

The book series Modeling and Optimization in Science and Technologies ( MOST ) publishes basic principles as well as novel theories and methods in the fast-evolving field of modeling and optimization. Topics of interest include, but are not limited to: methods for analysis, design and control of complex systems, networks and machines; methods for analysis, visualization and management of large data sets; use of supercomputers for modeling complex systems; digital signal processing; molecular modeling; and tools and software solutions for different scientific and technological purposes. Special emphasis is given to publications discussing novel theories and practical solutions that, by overcoming the limitations of traditional methods, may successfully address modern scientific challenges, thus promoting scientific and technological progress. The series publishes monographs, contributed volumes and conference proceedings, as well as advanced textbooks. The main targets of the series are graduate students, researchers and professionals working at the forefront of their fields.

More information about this series at http://www.springer.com/series/10577

This Springer imprint is published by the registered company Springer Nature Switzerland AG

The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Digital image processing mainly focuses on the research of signal processing, such as image contrast adjustment, image coding, image denoising and filtering. It is different that Image analysis emphasizes describing images with symbolic representations, analysis, interpretation, and recognition. Along with the boom in artificial intelligent and deep learning, digital image processing is going deeper and more advanced. People start the researches in simulating the human vision to see, to understand, and even to explain the real world using three techniques: image segmentation, image analysis, and image understanding. The Image segmentation is to extract the features such as the edges and regions for image analyzing, recognition, and understanding. Image analysis is to extract intelligent information from underlying features and their relationship using mathematical models and Image processing techniques. Image analysis and image processing are closely related. Although there may be a certain degree of overlapping, they are different in essence. Therefore, image analysis is more related to pattern recognition and computer vision. It is generally used to analyze the underlying features and superstructures by some mathematical models. The researches of image analysis are mainly focused on content-based image retrieval, face recognition, emotion recognition, optical character recognition, handwriting recognition, biomedical image analysis, video object extraction. The Image understanding is to further understand the meanings and scenario explanations by researching the properties and relations of the features and objects. The objects for image understanding are symbols from description; the process is similar to human brain.

Corresponding to image analysis, video analysis is to analyze the video frames of surveillance camera using computer vision techniques. It is also able to filter the background such as wind, rain, snow, fallen leaves, birds, and floating flags. It is so called object tracking in complex background. Due to the variant illusion, motion, occlusion, color, and complex background, the difficulty of object detection and tracking algorithm design is increased.

The steps in image and video analysis mainly include segmentation, classification, and explanation. The classification process normally extracts the features by SIFT and LBP. With the use of deep learning techniques, people start using deep feature by extracting automatically for image classification, scenario classification, and behaviors analysis.