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This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.
Computer vision --- Context-aware computing --- Pattern recognition systems --- Methodology. --- Data processing. --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Context-aware pervasive systems --- Context-awareness (Computer science) --- Ubiquitous computing --- Global system for mobile communications --- Mobile computing --- Sensor networks --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Computer vision. --- Multimedia systems. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Image Processing and Computer Vision. --- Multimedia Information Systems. --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Optical data processing. --- Multimedia information systems. --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment
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The book focuses on an image processing technique known as binarization. It provides a comprehensive survey over existing binarization techniques for both document and graphic images. A number of evaluation techniques have been presented for quantitative comparison of different binarization methods. The book provides results obtained comparing a number of standard and widely used binarization algorithms using some standard evaluation metrics. The comparative results presented in tables and charts facilitates understanding the process. In addition to this, the book presents techniques for preparing a reference image which is very much important for quantitative evaluation of the binarization techniques. The results are produced taking image samples from standard image databases.
Engineering. --- Signal, Image and Speech Processing. --- Computer vision. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Construction --- Industrial arts --- Technology --- Image Processing and Computer Vision. --- Computational Intelligence. --- Signal processing. --- Image processing. --- Speech processing systems. --- Optical data processing. --- Computational intelligence. --- Intelligence, Computational --- Soft computing --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Optical equipment
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This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.
Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- beeldverwerking --- object recognition --- computers --- grafische vormgeving --- landbouw --- multimedia --- computerkunde
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The book focuses on an image processing technique known as binarization. It provides a comprehensive survey over existing binarization techniques for both document and graphic images. A number of evaluation techniques have been presented for quantitative comparison of different binarization methods. The book provides results obtained comparing a number of standard and widely used binarization algorithms using some standard evaluation metrics. The comparative results presented in tables and charts facilitates understanding the process. In addition to this, the book presents techniques for preparing a reference image which is very much important for quantitative evaluation of the binarization techniques. The results are produced taking image samples from standard image databases.
Applied physical engineering --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- neuronale netwerken --- beeldverwerking --- fuzzy logic --- cybernetica --- KI (kunstmatige intelligentie) --- ingenieurswetenschappen --- signaalverwerking
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