Image Processing and Analysis in Sensor-Based Object Detection

Dear Colleagues,

Recent progress in sensor technologies—ranging from optical, infrared, and event cameras to LiDAR, radar, and multispectral devices—has significantly expanded the possibilities for object detection in real-world scenarios. Image processing and analysis represent the core of these advancements, enabling the accurate and efficient extraction of meaningful information from raw sensor data. Modern approaches combine classical computer vision methods with deep learning techniques to address challenges such as occlusion, varying illumination, real-time performance, and multi-modal data fusion. This Special Issue seeks original research and reviews that explore innovative algorithms and frameworks, and their applications in sensor-based object detection. Potential contributions may include novel data-preprocessing strategies, feature extraction methods, fusion of heterogeneous sensor data, and the deployment of these methods in fields such as autonomous vehicles, robotics, environmental monitoring, and smart surveillance.

This topic aligns with the scope of Sensors by focusing on the integration of sensing devices with advanced image analysis methods to improve the detection, classification, and interpretation of objects in diverse environments, enhancing both the capabilities of sensors and the impacts of their application.

Dr. Ruichao Hou
Dr. Kangjian He
Guest Editors

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