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050 4 _aTS171.57
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072 7 _aCOM067000
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100 1 _aMohaideen Abdul Kadhar, K.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982220
245 1 0 _aIndustrial Vision Systems with Raspberry Pi
_h[electronic resource] :
_bBuild and Design Vision products Using Python and OpenCV /
_cby K. Mohaideen Abdul Kadhar, G. Anand.
250 _a1st ed. 2024.
264 1 _aBerkeley, CA :
_bApress :
_bImprint: Apress,
_c2024.
300 _aXX, 331 p. 118 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
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347 _atext file
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490 1 _aMaker Innovations Series,
_x2948-2550
505 0 _aChapter 1: Introduction to Industrial Vision Systems -- Chapter 2: Raspberry Pi and required software -- Chapter 3: OpenCV - Python -- Chapter 4: Challenges in Industrial Vision Systems -- Chapter 5: Image Processing using OpenCV -- Chapter 6: Graphical User Interface with OpenCV and tkinter -- Chapter 7: Feature Detection and Matching -- Chapter 8: Image segmentation -- Chapter 9: Optical Character Recognition -- Chapter 10: Machine learning techniques for vision applications -- Chapter 11: Industrial Vision system Applications.
520 _aToday’s industries are faced with a growing demand for vision systems due to their non-invasive characteristics in inspecting product quality. These systems identify surface defects and faults, and verify components’ orientation and their measurements, etc. This book explores the vision techniques needed to design and develop your own industrial vision system with the help of Raspberry Pi. You’ll start by reviewing basic concepts and applications of machine vision systems, followed by the preliminaries of Python, OpenCV, required libraries, and installing OpenCV for Python on Raspberry Pi. These are used when implementing image processing for the system applications. You’ll then look at interfacing techniques and some of the challenges industrial vision systems encounter, such as lighting and camera angles. Algorithms and image processing techniques are also discussed, along with machine learning and deep learning techniques. Later chapters explain the use of GUI apps and real-time applications of Industrial vision systems. Each chapter concludes with examples and demo implementations to facilitate your knowledge of the concepts. By the end of the book, you’ll be able to build and deploy computer vision applications with Python, OpenCV, and Raspberry Pi. You will: Build and deploy industrial vision system using Raspberry Pi and Python programming Explore computer vision techniques using Raspberry Pi and OpenCV Implement popular vision techniques for industrial applications in real time Review modern image processing techniques such as image segmentation, thresholding, and contours.
650 0 _aMakerspaces.
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650 1 4 _aMaker.
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650 2 4 _aComputer Hardware.
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650 2 4 _aOperating Systems.
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700 1 _aAnand, G.
_eauthor.
_4aut
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_982221
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aMaker Innovations Series,
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856 4 0 _uhttps://doi.org/10.1007/979-8-8688-0097-9
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