Sensing Technologies in Image Processing and Pattern Recognition
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 161
Special Issue Editors
2. Computer Engineering Department, Epoka University, Tirana, Albania
Interests: intelligent systems; machine learning; intelligent distributed and multiagent systems; pattern recognition; communications and cybersecurity; image/signal processing and systems; biomedical systems
Interests: Image and video information processing; computer vision; information hiding; information security; Internet of Things (IoT) technologies; code cloning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The development of image processing and pattern recognition enables the extraction of meaningful information from visual data.
Image processing involves the manipulation and analysis of digital images using algorithms to enhance, restore, or extract features. It prepares raw image data for subsequent pattern recognition tasks by filtering noise, adjusting contrast, and segmenting images into meaningful regions.
Pattern recognition is the process of identifying and classifying patterns in data, often within the context of image processing. It relies on advanced algorithms that can discern and interpret structural regularities in visual data, such as faces, objects, or even abstract concepts like textures and shapes.
Sensing technologies in this domain harness various physical sensors (e.g., cameras, infrared detectors, and LiDAR) to capture images and other sensory information. These sensors, coupled with sophisticated software algorithms, enable the automatic detection, recognition, and analysis of patterns in real-world scenarios.
In summary, sensing technologies in image processing and pattern recognition represent a fusion of hardware and software innovations that enable the automated extraction and interpretation of meaningful information from visual data, with profound implications across industries from security and surveillance to healthcare and autonomous systems.
Prof. Dr. Dimitrios A. Karras
Prof. Dr. Yulin Wang
Guest Editors
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Keywords
- image recognition
- image acquisition
- image enhancement and restoration
- 3D modeling
- signal recognition
- intelligent sensors
- automated driving
- edge computing and intelligent sensing
- computer vision systems
- feature extraction
- human-computer interaction
- target detection and classification
- biometrics recognition
- image segmentation
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