Application of Information Theory to Computer Vision and Image Processing II
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: 25 February 2025 | Viewed by 10807
Special Issue Editors
Interests: fourth industrial revolution; artificial intelligence; cybersystems
Special Issues, Collections and Topics in MDPI journals
Interests: automated metrology; 3D coordinates measurement; robotic navigation; machine vision; simulation of the robotic swarms behaviour
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Interests: machine vision; stereo vision; systems laser; scanner control; digital image processing
Special Issues, Collections and Topics in MDPI journals
Interests: machine vision; stereo vision; systems laser; scanner control; analogic and digital processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to announce that due to the great success of “Application of Information Theory to Computer Vision and Image Processing”, a new Special Issue titled “Application of Information Theory to Computer Vision and Image Processing II” is open to continue the inclusion of relevant papers of related topics.
The application of information theory to computer vision and image processing has significantly contributed to advancing the understanding and capabilities of computer science. Mathematics methods are applied to signal and image processing for quantifying and obtaining accurate information with enhanced efficiency upon every innovation. Providing valuable tools and techniques for the development of intelligent and adaptive machine vision systems for measuring and analyzing the amount of information contained within a signal and an image, including the entropy theory to estimate the average amount of uncertainty or randomness in a dataset, where a high entropy indicates a higher level of unpredictability, while low entropy suggests a more predictable and structured dataset.
This Special Issue aims to publish information theory, measurement methods, data processing, tools, and techniques for the design and instrumentation used in machine vision systems by the application of computer vision and image processing, for analyzing, processing, and understanding visual data based on principles of information content, redundancy, and statistical properties.
Dr. Wendy Flores-Fuentes
Dr. Oleg Sergiyenko
Prof. Dr. Julio Cesar Rodríguez-Quiñonez
Dr. Jesús Elías Miranda-Vega
Guest Editors
Manuscript Submission Information
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Keywords
- information theory
- entropy and coding theory (data compression, watermark, minimizing data loss, visual information in a more compact form, transmission, storage)
- computer vision (identify relevant features and patterns)
- machine vision (data analysis and understanding, segmentation, registration, denoising and restoration, object recognition, classification and tracking)
- cyber-physical systems
- instrumentation
- signal and image processing
- measurements (3D spatial coordinates, redundancy, statistical properties)
- artificial intelligence
- applications (navigation, surveillance, facial recognition, medicine, robotics, entertainment, and more)
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