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|a 018005591
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|b O95 2015
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|2 23
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|a UAMI
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100 |
1 |
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|a Özkaya, Özen,
|e author.
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1 |
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|a Arduino computer vision programming :
|b design and develop real-world computer vision applications with the powerful combination of OpenCV and Arduino /
|c Özen Özkaya, Giray Yıllıkçı.
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|a Design and develop real-world computer vision applications with the powerful combination of OpenCV and Arduino
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264 |
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|a Birmingham, UK :
|b Packt Publishing,
|c 2015.
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300 |
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|a 1 online resource :
|b illustrations
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
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|a Community experience distilled
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|a Includes index.
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|a Cover ; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: General Overview of Computer Vision Systems ; Introducing computer vision systems; Approaching computer vision problems; Data acquisition; Preprocessing; Feature extraction by image processing; Post-processing and post-filtering; Recognition or detection; Acting in the real world; Connecting the pieces; Summary; Chapter 2: Fundamentals and Installation of OpenCV ; Fundamentals of OpenCV; The installation of OpenCV; Installing OpenCV on Linux.
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|a Installing and configuring packagesUsing OpenCV with Eclipse CDT; Installing OpenCV on Mac OS; Getting command-line tools; Installing HomeBrew; Using OpenCV in Xcode; Installing OpenCV on Windows; Installing MS Visual Studio 2013; OpenCV on iOS; OpenCV on Android; Installing OpenCV4Android; Eclipse integration; Running samples; Summary; Chapter 3: Data Acquisition with OpenCV and Arduino ; Image and video acquisition; Camera selection; Resolution; Color capabilities; Frame rate; 2D or 3D; Communication interface; Image acquisition; Reading a static image; Taking a snapshot from a webcam.
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|a Getting a video stream from the webcamInteraction with Kinect; Integration of Kinect with OpenCV; Sensor data acquisition; Setting up an Arduino environment; Fundamentals of sensors; Sensor types; Sampling theorem; Dealing with noise; Reading data from the temperature sensor; Summary; Chapter 4: Filtering Data with OpenCV ; Getting started with filtering; 2D convolution; Spatial domain filtering; Smoothing; Sharpening; Color conversions; Grayscale; Binary; Constant thresholding; Adaptive thresholding; Morphological filters; Erosion and dilation; Erosion; Dilation; Opening and closing; Closing.
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|a OpeningGradients and edge detection; The Canny edge detector; Laplacian of Gaussian filter; Sobel; Custom filtering; Histogram equalization; Chapter project; Summary; Chapter 5: Processing Vision Data with OpenCV ; Extracting features; Using basic statistics; Using color features; Using template matching features; Using contours; Using the convex hull; Using moments; Using the Hough transform; Using corners; Using SIFT; Using SURF; Using ORB; Using blob analysis; Summary; Chapter 6: Recognition with OpenCV ; Building applications which can think; Template matching; Feature matching.
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|a FLANN-based matchingUsing cascade classifiers; Using support vector machines; Summary; Chapter 7: Communicating with Arduino Using OpenCV ; Communicating with Arduino; Wired communications; Communicating via USB; Communicating via the serial port; Communicating via Ethernet; Wireless communications; Communicating via Bluetooth Low Energy; Communicating via ZigBee; Communicating via Wi-Fi; Communicating via radio frequency; Communicating with Java; Communicating with C++; Summary; Chapter 8: Acting in the Real World with Arduino ; Interfacing electric motors; Driving DC motors.
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|a Online resource; title from digital title page (viewed on April 03, 2018).
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|a Design and develop real-world computer vision applications with the powerful combination of OpenCV and Arduino About This Book Load and run the applications in Arduino to develop intelligent systems Design and implement detection, classification, and recognition algorithms for computer vision applications Explore the best practices of computer vision development including state of the art algorithms and hands-on example projects Who This Book Is For If you are a consumer and hobbyist who has familiarity with the basics of Arduino and wish to learn computer vision programming with Arduino to create intelligent systems, then this book is for you. No knowledge of computer vision programming is required. What You Will Learn Understand the design blocks and the generic architecture of computer vision systems by learning an efficient approach to modelling Build up your skill set of computer vision system design using OpenCV by learning fundamentals, camera selection, data acquisition, filtering, processing, feature extraction and recognition for any specific problem Learn the wired and wireless communication capabilities of Arduino and comprehensive best practices to connect it to the OpenCV environment in a platform-independent way Discover how to use Arduino to elegantly interact with real life via physical actions Solidify everything you've learnt by designing and building a computer vision-enabled practical robot from scratch In Detail Most technologies are developed with an inspiration of human capabilities. Most of the time, the hardest to implement capability is vision. Development of highly capable computer vision applications in an easy way requires a generic approach. In this approach, Arduino is a perfect tool for interaction with the real world. Moreover, the combination of OpenCV and Arduino boosts the level and quality of practical computer vision applications. Computer vision is the next level of sensing the environment. The purpose of this book is to teach you how to develop Arduino-supported computer vision systems that can interact with real life by seeing it. This book will combine the powers of Arduino and computer vision in a generalized, well-defined, and applicable way. The practices and approaches in the book can be used for any related problems and on any platforms. At the end of the book, you should be able to solve any types of real life vision problems with all its components by using the presented approach. Each componen ...
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546 |
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