Industrial Vision Systems with Raspberry Pi: Build and Design Vision Products Using Python and Opencv

Today'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.

What You'll Learn

• 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

Who This Book Is For

Raspberry Pi and Python enthusiasts interested in computer vision applications; educators, industrialists, and industrial solution providers who want to design vision-based testing products with the help of Raspberry Pi

如今的工業界面臨著對視覺系統的日益增長需求，因為這些系統在檢測產品質量時具有非侵入性的特點。這些系統可以識別表面缺陷和故障，驗證零件的方向和尺寸等。本書探討了設計和開發自己的工業視覺系統所需的視覺技術，並借助Raspberry Pi的幫助。

您將首先回顧機器視覺系統的基本概念和應用，然後介紹Python、OpenCV、所需的庫以及在Raspberry Pi上安裝Python的OpenCV。這些將在系統應用的圖像處理中使用。然後，您將研究接口技術以及工業視覺系統遇到的一些挑戰，例如照明和攝像頭角度。

本書還討論了算法和圖像處理技術，以及機器學習和深度學習技術。後面的章節解釋了GUI應用程序的使用以及工業視覺系統的實時應用。每章結尾都有示例和演示實現，以幫助您理解概念。

通過閱讀本書，您將能夠使用Python、OpenCV和Raspberry Pi構建和部署計算機視覺應用程序。

本書的學習目標包括：
- 使用Raspberry Pi和Python編程構建和部署工業視覺系統
- 使用Raspberry Pi和OpenCV探索計算機視覺技術
- 實時實現工業應用中常用的視覺技術
- 回顧現代圖像處理技術，如圖像分割、閾值處理和輪廓

本書適合Raspberry Pi和Python愛好者，對計算機視覺應用感興趣的教育工作者、工業界人士和工業解決方案提供商，他們希望借助Raspberry Pi設計基於視覺的測試產品。

Dr. K. Mohaideen Abdul Kadhar completed his Undergraduate degree in Electronics and Communication Engineering and his M.Tech with a specialization in Control and Instrumentation in 2005. In 2015, he obtained a Ph.D. in Control System Design using evolutionary algorithms. He has more than 16 years of experience in teaching and research. His area of interests includes Robust control systems, Optimization techniques, computer vision and image processing, data science, python programming, and working with Raspberry Pi boards. He is currently developing customized industrial vision systems for various industrial requirements. He has been a consultant for several industries in developing machine vision systems for industrial applications, a master trainer, and delivered workshops in the control systems, computer vision, image processing, optimization techniques, data science and Python programming.

G. Anand completed his Undergraduate degree in Electronics and Communication Engineering in 2008 and his Postgraduate Degree (M.E) in Communication Systems in 2011. He has more than 10 years of experience in teaching and research. His areas of interest include Signal Processing, Image processing, Vision system, Python programming, Data science, and Machine Learning. He has also delivered workshops in signal processing, image processing and python programming.

Dr. K. Mohaideen Abdul Kadhar於2005年完成了電子與通訊工程的學士學位，並在2005年獲得了控制與儀器專業的碩士學位。在2015年，他以進化算法設計控制系統為主題獲得了博士學位。他在教學和研究方面擁有超過16年的經驗。他的研究興趣包括強健控制系統、優化技術、計算機視覺和圖像處理、數據科學、Python編程以及與Raspberry Pi開發板的工作。他目前正在為各種工業需求開發定制的工業視覺系統。他曾擔任多家企業的顧問，為工業應用開發機器視覺系統，並擔任過主要培訓師，並在控制系統、計算機視覺、圖像處理、優化技術、數據科學和Python編程方面進行過工作坊的講授。

G. Anand於2008年完成了電子與通訊工程的學士學位，並在2011年獲得了通訊系統的碩士學位。他在教學和研究方面擁有超過10年的經驗。他的研究領域包括信號處理、圖像處理、視覺系統、Python編程、數據科學和機器學習。他還曾在信號處理、圖像處理和Python編程方面進行過工作坊的講授。