Traditional surveillance systems struggle to process large volumes of visual data, identify specific objects or behaviors, and adapt to dynamic environments. Computational intelligence, which encompasses techniques like artificial intelligence (AI), machine learning (ML), and computer vision, offers powerful tools to address these challenges by enabling automated analysis, pattern recognition, and decision-making based on visual data. Computational Intelligence in Surveillance Systems Using Image Processing addresses the unique challenges and ethical considerations of applying AI and ML, offering a nuanced understanding of the regulatory landscape. It provides insights into the responsible development and deployment of technologies to unlock the transformative potential of computational intelligence to revolutionize surveillance systems and advance the capabilities of security and monitoring across various sectors.
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1. Introduction to Computational Intelligence in Surveillance
2. Fundamentals of Image Processing for Surveillance
3. Role of Computational Intelligence in Surveillance
4. Overview of computer vision techniques for object detection, tracking, and recognition
5. Types of Surveillance Systems
6. Image Acquisition and Preprocessing
7. Object Detection and Recognition
8. Behavior Analysis and Anomaly Detection
9. Applications of anomaly detection algorithms in identifying abnormal events
10. Real-time Processing and Decision-making
11. Implementing decision-making algorithms for automated responses
12. Future Trends and Innovations
13. Integration with IoT and Smart Systems
14. Interoperability of computational intelligence with smart city infrastructure.
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Investigates the benefits and issues that arise when implementing and integrating computational intelligence techniques into surveillance infrastructure to improve accuracy, responsiveness, and scalability.
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Discusses emerging trends, potential challenges, and areas for future research, providing a roadmap for scholars looking to contribute to the evolving field of image processing
Explains how AI and ML algorithms can be applied to analyze and interpret visual data captured by surveillance cameras
Considers the challenges and considerations associated with deploying computational intelligence in surveillance, including privacy concerns, ethical considerations, and technical limitations
Explores specific use cases and applications where computational intelligence can enhance surveillance capabilities, such as object detection, activity recognition, anomaly detection, and predictive analytics
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Produktdetaljer
ISBN
9780443364082
Publisert
2026-03-01
Utgiver
Elsevier - Health Sciences Division
Vekt
450 gr
Høyde
235 mm
Bredde
191 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
350