Mastering OpenCV 4: A comprehensive guide to building computer vision and image processing applications with C++, 3/e (Paperback)

Roy Shilkrot, David Millan Escriva

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商品描述

Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms

Key Features

  • Learn about the new features that help unlock the full potential of OpenCV 4
  • Build face detection applications with a cascade classifier using face landmarks
  • Create an optical character recognition (OCR) model using deep learning and convolutional neural networks

Book Description

Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks.

You'll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You'll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You'll also go beyond the basics of computer vision to implement solutions for complex image processing projects.

By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.

What you will learn

  • Build real-world computer vision problems with working OpenCV code samples
  • Uncover best practices in engineering and maintaining OpenCV projects
  • Explore algorithmic design approaches for complex computer vision tasks
  • Work with OpenCV's most updated API (v4.0.0) through projects
  • Understand 3D scene reconstruction and Structure from Motion (SfM)
  • Study camera calibration and overlay AR using the ArUco Module

Who this book is for

This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.

Table of Contents

  1. Cartoonifier and Skin Color Analysis on the RaspberryPi
  2. Exploring Structure from Motion with the SfM Module
  3. Face Landmark and Pose Estimation with the Face Module
  4. Number Plate Recognition with Deep Convolutional Networks
  5. Face Recognition with the DNN Module
  6. Introduction to Web Computer Vision with OpenCv.js
  7. Android Camera Calibration and AR using the ARUco Module
  8. iOS Image Stitching with the Stitching Module
  9. Finding the Best OpenCV Algorithm for the Job
  10. Avoiding Common Pitfalls in OpenCV

商品描述(中文翻譯)

進行實際的計算機視覺專案,涵蓋先進的物體檢測技術以及現代深度學習和機器學習算法

主要特點


  • 了解幫助發揮 OpenCV 4 全部潛力的新功能

  • 使用面部特徵點的級聯分類器構建面部檢測應用程式

  • 使用深度學習和卷積神經網絡創建光學字符識別(OCR)模型

書籍描述

《精通 OpenCV》第三版針對初學者的計算機視覺工程師,致力於精通 OpenCV。書中將數學公式降到最低限度,提供從構思到運行代碼的完整項目,涵蓋當前計算機視覺熱門話題,如人臉識別、特徵點檢測和姿態估計,以及使用深度卷積網絡進行數字識別。

你將從經驗豐富的 OpenCV 專家那裡學習如何在學術界和工業界實現計算機視覺產品和項目。你將熟悉 API 功能,並深入了解完整計算機視覺項目中的設計選擇。你還將超越計算機視覺的基礎,實現複雜圖像處理項目的解決方案。

通過閱讀本書,你將通過書中的項目創建各種工作原型,並熟悉 OpenCV4 的新功能。

你將學到什麼


  • 使用實際的 OpenCV 代碼示例解決真實世界的計算機視覺問題

  • 揭示工程和維護 OpenCV 項目的最佳實踐

  • 探索複雜計算機視覺任務的算法設計方法

  • 通過項目使用 OpenCV 最新的 API(v4.0.0)

  • 了解三維場景重建和運動結構(SfM)

  • 研究相機校準並使用 ArUco 模塊進行增強現實(AR)

適合閱讀對象

本書適合具備基本 OpenCV 知識並具備 C++ 編程能力的讀者。你需要對一些更理論/數學概念有一定的理解,因為本書進展相當迅速。

目錄


  1. 在 RaspberryPi 上進行卡通化和皮膚顏色分析

  2. 使用 SfM 模塊探索運動結構

  3. 使用面部模塊進行面部特徵點和姿態估計

  4. 使用深度卷積網絡進行車牌識別

  5. 使用 DNN 模塊進行人臉識別

  6. 介紹使用 OpenCv.js 的 Web 計算機視覺

  7. 使用 ARUco 模塊進行 Android 相機校準和 AR

  8. 使用 Stitching 模塊在 iOS 上進行圖像拼接

  9. 找到最適合工作的 OpenCV 算法

  10. 避免在 OpenCV 中常見的問題