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Techniques for the Automated Segmentation of Lung in Thoracic Computed Tomography Scans

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DOI: 10.4018/978-1-4666-3994-2.ch035
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Sensakovic, William F. and Samuel G. Armato. "Techniques for the Automated Segmentation of Lung in Thoracic Computed Tomography Scans." Image Processing: Concepts, Methodologies, Tools, and Applications. IGI Global, 2013. 675-687. Web. 31 Jul. 2014. doi:10.4018/978-1-4666-3994-2.ch035


Sensakovic, W. F., & Armato, S. G. (2013). Techniques for the Automated Segmentation of Lung in Thoracic Computed Tomography Scans. In I. Management Association (Ed.), Image Processing: Concepts, Methodologies, Tools, and Applications (pp. 675-687). Hershey, PA: Information Science Reference. doi:10.4018/978-1-4666-3994-2.ch035


Sensakovic, William F. and Samuel G. Armato. "Techniques for the Automated Segmentation of Lung in Thoracic Computed Tomography Scans." In Image Processing: Concepts, Methodologies, Tools, and Applications, ed. Information Resources Management Association, 675-687 (2013), accessed July 31, 2014. doi:10.4018/978-1-4666-3994-2.ch035

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Techniques for the Automated Segmentation of Lung in Thoracic Computed Tomography Scans
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Computed Tomography (CT) is widely used to diagnose and assess thoracic diseases. The improved resolution of CT studies has resulted in a substantial increase of image data for analysis by radiologists. The time-consuming nature of this analysis motivates the application of Computer-Aided Diagnostic (CAD) methods to assist radiologists. Most CAD methods require identification of the lung within the patient images, a preprocessing step known as “lung segmentation.” This chapter describes an intensity-based lung segmentation method. The segmentation method begins with simple thresholding, and several image processing modules are included to improve segmentation accuracy and robustness. Common segmentation difficulties are discussed and motivate the inclusion of each module in the lung segmentation method. These modules will include brief explanations of common techniques (e.g., morphological operators) in addition to novel techniques developed specifically for lung segmentation (e.g., gradient correlation filters).
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Computed Tomography (CT) of the thorax is used to diagnose and assess numerous thoracic diseases such as mesothelioma, emphysema, pulmonary embolism, and lung nodules (Armato & Sensakovic, 2004; Morgan, 1992; Mastuani, MacMahon, & Doi, 2002; Sensakovic,, et al., 2011; Zhou, et al., 2005). The availability of multidetector-row, fan-beam, and cone-beam CT scanners has improved image resolution and decreased scanning time, thus expanding the role of CT in the diagnostic assessment of patients. The improved resolution has resulted in substantially larger amounts of image data that must be analyzed by the radiologist or clinician. It is the tedious and time-consuming nature of this data analysis that has motivated the development of Computer-Aided Diagnostic (CAD) methods to assist radiologists in the evaluation of CT scans.

CAD methods that are applied to CT scans of the thorax usually require identification of scan voxels that comprise the lung (i.e., lung segmentation). The purpose of lung segmentation is threefold. First, many thoracic diseases such as nodules and emphysema are located in the lung. Lung segmentation allows a CAD method or image-guided therapy system to focus on analyzing only those voxels that comprise the lung, thus reducing the potential for errors (e.g., misdiagnosis of aortic calcification as a lung nodule). Further, limiting processing to the lungs greatly reduces computation time, because the lungs occupy only a fraction of the total thoracic CT scan. Second, the lungs are prominent, high-contrast structures centrally located within the thorax and thus may be used as guides for the segmentation of other structures of interest such as the heart or pleura (Sensakovic, 2010). Finally, lung segmentation may be useful for image data visualization. The three-dimensional (3D) display of CT scans is an area of rapid development, and lung segmentation would be required in a situation where, for example, a volume-rendered version of the lung parenchyma is desired as a visual aid for surgical planning (Wei, Hu, MacGregor, & Gelfand, 2006).

Lung segmentation must be accurate because abnormalities such as lung nodules may exist at the extreme periphery of the lungs. If the entire lung is not segmented, such abnormalities will be lost to subsequent analyses (Armato & Sensakovic, 2004). Quantitative assessment of lung volume (Sensakovic, Armato, Starkey, Kindler, & Vigneswaran, 2010) is a means of assessing several diseases, and inaccurate measurements could result in incorrect assessment. Finally, segmentation of pleural disease will often use the lung segmentation to establish the boundary of the pleura (and thus the disease boundary). Inaccurate segmentation of the lung will result in an incorrect segmentation (and assessment) of pleural disease (Sensakovic, 2010).

Lung segmentation in CT scans is one of the most extensively researched areas in medical image processing (Sluimir, et al. 2006). The low density of lung parenchyma compared with surrounding soft tissue translates into high contrast on CT, which in turn facilitates the use of several image processing techniques such as histogram thresholding (Armato & Sensakovic, 2004), active contours (Cohen, 1991; Kass, Witkin, & Terzopoulos, 1988), models (Brown, 1997), and graph cuts (Massoptier, 2009). This chapter describes an intensity-based lung segmentation method. The segmentation method begins with simple thresholding, and several image processing modules are included to improve segmentation accuracy and robustness. Common segmentation difficulties are discussed and motivate the inclusion of each module in the lung segmentation method.


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Table of Contents
Chapter 1
Image Analysis  (pages 1-14)
Detlev Droege
This chapter focuses on the image processing part of eye tracking systems. Basic knowledge of image processing is assumed. After an overview of the... Sample PDF
Image Analysis
Chapter 2
G.A. Papakostas, E.G. Karakasis, D.E. Koulouriotis
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Orthogonal Image Moment Invariants: Highly Discriminative Features for Pattern Recognition Applications
Chapter 3
Radu Dobrescu, Dan Popescu
Image processing operations have been classified into three main levels, namely low (primary), intermediate, and high. In order to combine speed and... Sample PDF
Real-Time Primary Image Processing
Chapter 4
Pierre-Emmanuel Leni, Yohan D. Fougerolle, Frédéric Truchetet
In 1900, Hilbert stated that high order equations cannot be solved by sums and compositions of bivariate functions. In 1957, Kolmogorov proved this... Sample PDF
The Kolmogorov Spline Network for Image Processing
Chapter 5
Yiqun Hu, Viswanath Gopalakrishnan, Deepu Rajan
Visual saliency, which distinguishes “interesting” visual content from others, plays an important role in multimedia and computer vision... Sample PDF
Modeling Visual Saliency in Images and Videos
Chapter 6
S. K. Maharana, Ganesh Prabhakar P., Amit Bhati
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A Study of Cloud Computing for Retinal Image Processing through MATLAB
Chapter 7
Graziano Chesi, Yeung Sam Hung
Triangulation is a fundamental problem in computer vision that consists of estimating the 3D position of a point of the scene from the estimates of... Sample PDF
Certain and Uncertain Triangulation in Multiple Camera Vision Systems via LMIs
Chapter 8
Rimon Elias
This chapter surveys many fundamental aspects of projective geometry that have been used extensively in computer vision literature. In particular... Sample PDF
Projective Geometry for 3D Modeling of Objects
Chapter 9
Peng Song, Xiaojun Wu
3D modeling of complex objects is an important task of computer graphics and poses substantial difficulties to traditional synthetic modeling... Sample PDF
Multi-View Stereo Reconstruction Technique
Chapter 10
Muhammad Tariq Mahmood, Tae-Sun Choi
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Image Focus Measure Based on Energy of High Frequency Components in S-Transform
Chapter 11
Yuexing Han, Bing Wang, Hideki Koike, Masanori Idesawa
One of the main goals of image understanding and computer vision applications is to recognize an object from various images. Object recognition has... Sample PDF
Object Recognition with a Limited Database Using Shape Space Theory
Chapter 12
Bin Ma, Chun-lei Li, Yun-hong Wang, Xiao Bai
Visual saliency, namely the perceptual significance to human vision system (HVS), is a quality that differentiates an object from its neighbors.... Sample PDF
Salient Region Detection for Biometric Watermarking
Chapter 13
Ekta Walia, Anu Suneja
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Fast and High Capacity Digital Image Watermarking Technique Based on Phase of Zernike Moments
Chapter 14
Radu Dobrescu, Dan Popescu
Texture analysis research attempts to solve two important kinds of problems: texture segmentation and texture classification. In some applications... Sample PDF
Image Processing Applications Based on Texture and Fractal Analysis
Chapter 15
Jonathan Delcourt, Alamin Mansouri, Tadeusz Sliwa, Yvon Voisin
This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different... Sample PDF
An Evaluation Framework and a Benchmark for Multi/Hyperspectral Image Compression
Chapter 16
Pearl P. Guan, Hong Yan
Image thresholding and edge detection are crucial in image processing and understanding. In this chapter, the authors propose a hierarchical... Sample PDF
A Hierarchical Multilevel Image Thresholding Method Based on the Maximum Fuzzy Entropy Principle
Chapter 17
Koushik Mondal
Image segmentation and subsequent extraction from a noise-affected background, has all along remained a challenging task in the field of image... Sample PDF
A Novel Fuzzy Rule Guided Intelligent Technique for Gray Image Extraction and Segmentation
Chapter 18
Charles-Edmond Bichot
Image segmentation is an important research area in computer vision and its applications in different disciplines, such as medicine, are of great... Sample PDF
Unsupervised and Supervised Image Segmentation Using Graph Partitioning
Chapter 19
Yuchi Huang
This chapter explores original techniques for the construction of hypergraph models for computer vision applications. A hypergraph is a... Sample PDF
Hypergraph Based Visual Segmentation and Retrieval
Chapter 20
Horst Bunke, Kaspar Riesen
The domain of graphs contains only little mathematical structure. That is, most of the basic mathematical operations, actually required by many... Sample PDF
Graph Embedding Using Dissimilarities with Applications in Classification
Chapter 21
Mario Vento, Pasquale Foggia
Many computer vision applications require a comparison between two objects, or between an object and a reference model. When the objects or the... Sample PDF
Graph Matching Techniques for Computer Vision
Chapter 22
Matthieu Perreira Da Silva, Vincent Courboulay
In the field of scene analysis for computer vision, a trade-off must be found between the quality of the results expected and the amount of computer... Sample PDF
Implementation and Evaluation of a Computational Model of Attention for Computer Vision
Chapter 23
E. Antúnez, Y. Haxhimusa, R. Marfil, W. G. Kropatsch, A. Bandera
Computer vision systems have to deal with thousands, sometimes millions of pixel values from each frame, and the computational complexity of many... Sample PDF
Artificial Visual Attention Using Combinatorial Pyramids
Chapter 24
Pavel Zemcik, Michal Spanel, Premysl Krsek, Miloslav Richter
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Methods of 3D Object Shape Acquisition
Chapter 25
Erik Cuevas, Daniel Zaldivar, Marco Perez-Cisneros
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Corner Detection Using Fuzzy Principles
Chapter 26
Simon D. Thackray, Christos V. Bourantas, Poay H. Loh, Vasilios D. Tsakanikas, Dimitrios I. Fotiadis
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Optical Coherence Tomography Image Interpretation and Image Processing Methodologies
Chapter 27
Ganesh Naik, Dinesh Kant Kumar, Sridhar Arjunan
In recent times there is an urgent need for a simple yet robust system to identify natural hand actions and gestures for controlling prostheses and... Sample PDF
ICA as Pattern Recognition Technique for Gesture Identification: A Study Using Bio-Signal
Chapter 28
Ippei Torii, Yousuke Okada, Manabu Onogi, Naohiro Ishii
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Inexpensive, Simple and Quick Photorealistic 3DCG Modeling
Chapter 29
Vicente Morell-Gimenez, Sergio Orts-Escolano, José García-Rodríguez, Miguel Cazorla, Diego Viejo
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A Review of Registration Methods on Mobile Robots
Chapter 30
Laura Ruotsalainen, Heidi Kuusniemi
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Visual Positioning in a Smartphone
Chapter 31
S. Mohan, S. Murali
In computer vision, 3D modeling refers to the process of developing 3D representation of the real world objects with systematic procedure. The 3D... Sample PDF
Image Based 3D Modeling and Rendering from Single View Perspective Images
Chapter 32
Yoshitaka Masutani, Mitsutaka Nemoto, Yukihiro Nomura, Naoto Hayashi
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Clinical Machine Learning in Action: CAD System Design, Development, Tuning, and Long-Term Experience
Chapter 33
Antonis A. Sakellarios, Christos V. Bourantas, Lambros S. Athanasiou, Dimitrios I. Fotiadis, Lampros K. Michalis
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IVUS Image Processing Methodologies
Chapter 34
Anastasia Daskalaki, Kostas Giokas, Dimitris Koutsouris
In this paper, the authors describe a surgeon assistive Augmented Reality (AR) model for endoscopic procedures. They analyze the main parts of the... Sample PDF
Surgeon Assistive Augmented Reality Model with the use of Endoscopic Camera for Line of Vision Calculation
Chapter 35
William F. Sensakovic, Samuel G. Armato
Computed Tomography (CT) is widely used to diagnose and assess thoracic diseases. The improved resolution of CT studies has resulted in a... Sample PDF
Techniques for the Automated Segmentation of Lung in Thoracic Computed Tomography Scans
Chapter 36
Stanislaw Osowski, Michal Kruk, Robert Koktysz, Jaroslaw Kurek
This chapter presents the computerized system for automatic analysis of the medical image of the colon biopsy, able to extract the important... Sample PDF
Image Processing for Localization and Parameterization of the Glandular Ducts of Colon in Inflammatory Bowel Diseases
Chapter 37
D. Jude Hemanth, J. Anitha
Medical image classification is one of the most widely used methodologies in the biomedical field for abnormality detection in the anatomy of the... Sample PDF
Computational Intelligence Techniques for Pattern Recognition in Biomedical Image Processing Applications
Chapter 38
P. S. Hiremath, Iranna Y. Humnabad
The study of medical image analysis encompasses the various techniques for acquisition of images of biological structures pertaining to human body... Sample PDF
Color Image Segmentation of Endoscopic and Microscopic Images for Abnormality Detection in Esophagus
Chapter 39
Ahmad Taher Azar
Conventional mammography is considered the modality of choice for the detection of breast cancer. The process involves a human radiologist visually... Sample PDF
Statistical Analysis for Radiologists’ Interpretations Variability in Mammograms
Chapter 40
Hajar Mohammedsaleh H. Alharbi, Paul Kwan, Ashoka Jayawardena, A. S. M. Sajeev
In the last decade, many computer-aided diagnosis (CAD) systems that utilize a broad range of diagnostic techniques have been proposed. Due to both... Sample PDF
Fuzzy Image Segmentation for Mass Detection in Digital Mammography: Recent Advances and Techniques
Chapter 41
Bernadetta Kwintiana Ane, Dieter Roller
To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women in the world. Papanicolau smear test is a well-known... Sample PDF
Adaptive Intelligent Systems for Recognition of Cancerous Cervical Cells Based on 2D Cervical Cytological Digital Images
Chapter 42
Stephanie L. Davy-Jow, Summer J. Decker, Damian Schofield
Anthropology is the “study of man” and encompasses a diverse range of topics, including socio-cultural studies, linguistics, archaeology, and... Sample PDF
Virtual Forensic Anthropology: Applications of Advanced Computer Graphics Technology to the Identification of Human Remains
Chapter 43
Sanjeev S. Sannakki, Vijay S. Rajpurohit, V. B. Nargund, Arun R. Kumar, Prema S. Yallur
Plant Pathology is the scientific study of plant diseases, caused by pathogens and environmental conditions (physiological factors). Detection and... Sample PDF
Computational Intelligence for Pathological Issues in Precision Agriculture
Chapter 44
J. Blasco, N. Aleixos, S. Cubero, F. Albert, D. Lorente, J. Gómez-Sanchis
Nowadays, there is a growing demand for quality fruits and vegetables that are simple to prepare and consume, like minimally processed fruits. These... Sample PDF
In-Line Sorting of Processed Fruit Using Computer Vision: Application to the Inspection of Satsuma Segments and Pomegranate Arils
Chapter 45
Mehrtash Harandi, Javid Taheri, Brian C. Lovell
Recognizing objects based on their appearance (visual recognition) is one of the most significant abilities of many living creatures. In this study... Sample PDF
Machine Learning Applications in Computer Vision
Chapter 46
Hidehiko Hayashi, Akinori Minazuki
This chapter presents an objective assessment method of image quality using visual evoked potentials (VEPs) to image engineer field based on... Sample PDF
Study on Image Quality Assessment with Scale Space Approach Using Index of Visual Evoked Potentials
Chapter 47
Nikolaus Karpinsky, Song Zhang
As 3D becomes more ubiquitous with the advent of 3D scanning and display technology, methods of compressing and transmitting 3D data need to be... Sample PDF
3D Shape Compression Using Holoimage
Chapter 48
C.J. Prabhakar, P.U. Praveen Kumar, P.S. Hiremath
Over the last two decades, research community of computer vision has developed various techniques suitable for underwater applications using... Sample PDF
3D Reconstruction of Underwater Natural Scenes and Objects Using Stereo Vision
Chapter 49
David Pérez-Suárez, Paul A. Higgins, D. Shaun Bloomfield, R.T. James McAteer, Larisza D. Krista, Jason P. Byrne, Peter. T. Gallagher
The solar surface and atmosphere are highly dynamic plasma environments, which evolve over a wide range of temporal and spatial scales. Large-scale... Sample PDF
Automated Solar Feature Detection for Space Weather Applications
Chapter 50
Dariusz Jakóbczak
Object recognition is one of the topics of artificial intelligence, computer vision, image processing and machine vision. The classical problem in... Sample PDF
Object Recognition via Contour Points Reconstruction Using Hurwitz - Radon Matrices
Chapter 51
Rudra Narayan Hota, Kishore Jonna, P. Radha Krishna
Traffic congestion problem is rising day-by-day due to increasing number of small to heavy weight vehicles on the road, poorly designed... Sample PDF
Video Stream Mining for On-Road Traffic Density Analytics
Chapter 52
Jiang Yu Zheng
The innovative combination of wireless sensor network (WSN) technology with visual monitoring and surveillance technology in computer vision has... Sample PDF
Using Line Cameras for Monitoring and Surveillance Sensor Networks
Chapter 53
Raed Almomani, Ming Dong
Video tracking systems are increasingly used day in and day out in various applications such as surveillance, security, monitoring, and robotic... Sample PDF
Building a Multiple Object Tracking System with Occlusion Handling in Surveillance Videos
Chapter 54
Hai Thanh Nguyen, Katrin Franke, Slobodan Petrovic
Intrusion Detection Systems (IDSs) have become an important security tool for managing risk and an indispensable part of overall security... Sample PDF
Feature Extraction Methods for Intrusion Detection Systems
Chapter 55
Sreela Sasi
Computer vision plays a significant role in a wide range of homeland security applications. The homeland security applications include: port... Sample PDF
Security Applications Using Computer Vision
Chapter 56
Moi Hoon Yap, Hassan Ugail
The application of computer vision in face processing remains an important research field. The aim of this chapter is to provide an up-to-date... Sample PDF
Facial Image Processing in Computer Vision
Chapter 57
Patrycia Barros de Lima Klavdianos, Lourdes Mattos Brasil, Jairo Simão Santana Melo
Recognition of human faces has been a fascinating subject in research field for many years. It is considered a multidisciplinary field because it... Sample PDF
Face Recognition with Active Appearance Model (AAM)
Chapter 58
Zahid Riaz, Suat Gedikli, Michael Beetz, Bernd Radig
In this chapter, we focus on the human robot joint interaction application where robots can extract the useful multiple features from human faces.... Sample PDF
3D Face Modeling for Multi-Feature Extraction for Intelligent Systems
Chapter 59
Renato Ramos da Silva, Roseli Aparecida Francelin Romero
Computer vision is essential to develop a social robotic system capable to interact with humans. It is responsible to extract and represent the... Sample PDF
Computer Vision for Learning to Interact Socially with Humans
Chapter 60
Giancarlo Iannizzotto, Francesco La Rosa
This chapter introduces the VirtualBoard framework for building vision-based Perceptual User Interfaces (PUI). While most vision-based Human... Sample PDF
A Modular Framework for Vision-Based Human Computer Interaction
Chapter 61
Vladimir Devyatkov, Alexander Alfimtsev
A primary goal of virtual environments is to support natural, efficient, powerful and flexible human-computer interaction. But the traditional... Sample PDF
Human-Computer Interaction in Games Using Computer Vision Techniques
Chapter 62
Wenjie Yan, Elena Torta, David van der Pol, Nils Meins, Cornelius Weber, Raymond H. Cuijpers, Stefan Wermter
This chapter presents an overview of a typical scenario of Ambient Assisted Living (AAL) in which a robot navigates to a person for conveying... Sample PDF
Learning Robot Vision for Assisted Living
Chapter 63
Dan Grois, Ofer Hadar
The advent of cheaper and more powerful devices with the ability to play, create, and transmit video content has led to a dramatic increase in the... Sample PDF
Advances in Region-of-Interest Video and Image Processing
Chapter 64
Shaimaa A. El-said, Khalid F. A. Hussein, Mohamed M. Fouad
A novel Adaptive Lossy Image Compression (ALIC) technique is proposed to achieve high compression ratio by reducing the number of source symbols... Sample PDF
Image Compression Technique for Low Bit Rate Transmission
Chapter 65
Chao Zeng, Wenjing Jia, Xiangjian He, Min Xu
Image segmentation techniques using graph theory has become a thriving research area in computer vision community in recent years. This chapter... Sample PDF
Recent Advances on Graph-Based Image Segmentation Techniques
Chapter 66
Antonio J. Rodríguez-Sánchez, John K. Tsotsos
Computational models of visual processes are of interest in fields such as cybernetics, robotics, computer vision, and others. This chapter argues... Sample PDF
The Roles of Endstopped and Curvature Tuned Computations in a Hierarchical Representation of 2D Shape
Chapter 67
René Rosenbaum
With the focus being on digital imagery, this chapter proposes novel technology that is able to cope with the heterogeneous viewing hardware and... Sample PDF
Large Imagery on Small Screens: Novel Technology for Device Adaptation in Mobile Services
Chapter 68
Xiangrong Zhou, Hiroshi Fujita
Location of an inner organ in a CT image is the basic information that is required for medical image analysis such as image segmentation, lesion... Sample PDF
Automatic Organ Localization on X-Ray CT Images by Using Ensemble-Learning Techniques
Chapter 69
Shiv Ram Dubey, Anand Singh Jalal
Diseases in fruit cause devastating problem in economic losses and production in agricultural industry worldwide. In this paper, an adaptive... Sample PDF
Adapted Approach for Fruit Disease Identification using Images
Chapter 70
Gilles Gesquière, Alexis Manin
Due to the advances in computer graphics and improved network speed it is now possible to navigate in 3D virtual world in real time. Until now... Sample PDF
3D Visualization of Urban Data Based on CityGML with WebGL
Chapter 71
Michael G. Mauk
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Image Processing for Solar Cell Analysis, Diagnostics and Quality Assurance Inspection
Chapter 72
Abd El Rahman Shabayek, Olivier Morel, David Fofi
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Visual Behavior Based Bio-Inspired Polarization Techniques in Computer Vision and Robotics
Chapter 73
Gour Karmakar, Laurence S. Dooley, Nemai Chandra Karmakar, Joarder Kamruzzaman
Object analysis using visual sensors is one of the most important and challenging issues in computer vision research due principally to difficulties... Sample PDF
Object Analysis with Visual Sensors and RFID
Chapter 74
Zakia Hammal
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From Face to Facial Expression
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Replicating the Role of the Human Retina for a Cortical Visual Neuroprosthesis