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"Optical pattern recognition"
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Background modeling and foreground detection for video surveillance
Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements.Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection.
Book
Moments and moment invariants in pattern recognition
Moments as projections of an image's intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments. Considers invariants to traditional transforms - translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants. Reviews and extends a recent field of invariants with respect to convolution/blurring. Introduces implicit moment invariants as a tool for recognizing elastically deformed objects. Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments. Offers comprehensive advice on the construction of various invariants illustrated with practical examples. Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest.
eBook
Tunable All-Optical Pattern Recognition System Based on Nonlinear Optical Loop Mirror for Bit-Flip BPSK Targets
As the basic physical infrastructure of various networks, optical networks are crucial to the advancement of information technology. Meanwhile, as new technologies emerge, the security of optical networks is facing serious threats. To improve the security of optical networks, optoelectronic firewalls primarily leverage all-optical pattern recognition to perform direct detection and analysis of data transmitted through the optical network at the optical layer. However, the current all-optical pattern recognition system still faces some problems when deployed in optical networks, including phase-lockingand relatively low recognition efficiency and scalability. In this paper, we propose a tunable all-optical pattern recognition system based on a nonlinear optical loop mirror (NOLM) for bit-flip BPSK targets. The operational principles and simulation setup of the proposed system are comprehensively described. Numerical simulations demonstrate that the system can accurately recognize and determine the position of 4-bit and 8-bit bit-flip BPSK targets in 16-bit input data with tunable frequencies of 192.8 THz and 193.4 THz at a data rate of 100 Gbps. Finally, the impact of input noise is evaluated by extinction ratio (ER), contrast ratio (CR), Q factor, bit error rate (BER), amplitude modulation (AM), and signal-to-noise ratio (SNR) under both frequencies.
Journal Article
Optical Computing: Status and Perspectives
For many years, optics has been employed in computing, although the major focus has been and remains to be on connecting parts of computers, for communications, or more fundamentally in systems that have some optical function or element (optical pattern recognition, etc.). Optical digital computers are still evolving; however, a variety of components that can eventually lead to true optical computers, such as optical logic gates, optical switches, neural networks, and spatial light modulators have previously been developed and are discussed in this paper. High-performance off-the-shelf computers can accurately simulate and construct more complicated photonic devices and systems. These advancements have developed under unusual circumstances: photonics is an emerging tool for the next generation of computing hardware, while recent advances in digital computers have empowered the design, modeling, and creation of a new class of photonic devices and systems with unparalleled challenges. Thus, the review of the status and perspectives shows that optical technology offers incredible developments in computational efficiency; however, only separately implemented optical operations are known so far, and the launch of the world’s first commercial optical processing system was only recently announced. Most likely, the optical computer has not been put into mass production because there are still no good solutions for optical transistors, optical memory, and much more that acceptance to break the huge inertia of many proven technologies in electronics.
Journal Article
Template matching techniques in computer vision : theory and practice
The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems.
eBook
Optical nanomanipulation
The extended and updated second edition of this book expands its broad survey of the wide-ranging field of optical nanomanipulation. It aims to establish and differentiate the physical principles of this phenomenon, while providing a snapshot portrait of many of the most prominent and up-to-date applications.
eBook
Recognised and Harmed
Private face recognition technologies are increasingly entering the private and public sphere, with no adequate checks and balances. This comprehensive and important new reference work explores crucial regulatory challenges, stemming from the use of private face recognition technologies in Europe. After detecting technological neutrality in law, legal uncertainty in case law and the risk of over-surveillance, it recommends an ex ante and targeted classification approach with a view to minimising privacy harms. Under the proposed scheme, an expert agency can scrutinise a given technology, balance conflicting stakes, classify that technological use and, finally, give a 'go', 'no-go' or 'go-in-condition' decision, before its actual implementation in the real-world. Recommended for legal and technology researchers and scholars focusing on surveillance and privacy, as well as government, regulatory and civil rights agencies.
eBook