Python Image Processing Cookbook: Over 60 recipes to help you perform complex image processing and computer vision tasks with ease (Paperback)

Sandipan Dey

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商品描述

Explore Keras, scikit-image, open source computer vision (OpenCV), Matplotlib, and a wide range of other Python tools and frameworks to solve real-world image processing problems

Key Features

  • Discover solutions to complex image processing tasks using Python tools such as scikit-image and Keras
  • Learn popular concepts such as machine learning, deep learning, and neural networks for image processing
  • Explore common and not-so-common challenges faced in image processing

Book Description

With the advancements in wireless devices and mobile technology, there's increasing demand for people with digital image processing skills in order to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing.

With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as object detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques, such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning techniques such as transfer learning and fine-tuning to solve real-world problems.

By the end of this book, you'll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively.

What you will learn

  • Implement supervised and unsupervised machine learning algorithms for image processing
  • Use deep neural network models for advanced image processing tasks
  • Perform image classification, object detection, and face recognition
  • Apply image segmentation and registration techniques on medical images to assist doctors
  • Use classical image processing and deep learning methods for image restoration
  • Implement text detection in images using Tesseract, the optical character recognition (OCR) engine
  • Understand image enhancement techniques such as gradient blending

Who this book is for

This book is for image processing engineers, computer vision engineers, software developers, machine learning engineers, or anyone who wants to become well-versed with image processing techniques and methods using a recipe-based approach. Although no image processing knowledge is expected, prior Python coding experience is necessary to understand key concepts covered in the book.

商品描述(中文翻譯)

探索Keras、scikit-image、開源計算機視覺(OpenCV)、Matplotlib和其他Python工具和框架,以解決現實世界的圖像處理問題。

主要特點:

- 使用scikit-image和Keras等Python工具,發現解決複雜圖像處理任務的解決方案。
- 學習機器學習、深度學習和神經網絡等流行概念,用於圖像處理。
- 探索圖像處理中常見和不常見的挑戰。

書籍描述:

隨著無線設備和移動技術的進步,對具備數字圖像處理技能的人的需求越來越大,以從不斷增長的圖像數量中提取有用信息。本書全面介紹了相關工具和算法,並引導您進行圖像處理的分析和可視化。

通過60多個尖端的示例,您將解決圖像處理中的常見挑戰,並學習如何使用大型混合數據集執行複雜任務,例如對象檢測、圖像分割和圖像重建。專門的章節還將引導您實施各種圖像增強和圖像恢復技術,例如卡通化、梯度混合和稀疏字典學習。隨著您的進步,您將掌握面部變形和圖像分割技術。本書強調實用解決方案,將幫助您應用深度學習技術,如遷移學習和微調,解決現實世界的問題。

通過閱讀本書,您將能夠熟練地利用Python生態系統的能力,有效實施各種圖像處理技術。

您將學到什麼:

- 為圖像處理實施監督和非監督機器學習算法。
- 使用深度神經網絡模型進行高級圖像處理任務。
- 執行圖像分類、對象檢測和人臉識別。
- 在醫學圖像上應用圖像分割和配準技術,以協助醫生。
- 使用傳統圖像處理和深度學習方法進行圖像恢復。
- 使用Tesseract(光學字符識別引擎)在圖像中檢測文本。
- 理解梯度混合等圖像增強技術。

本書適合對象:

本書適合圖像處理工程師、計算機視覺工程師、軟件開發人員、機器學習工程師或任何希望通過基於配方的方法熟悉圖像處理技術和方法的人。雖然不需要圖像處理知識,但需要先前的Python編程經驗以理解本書中涵蓋的關鍵概念。

作者簡介

Sandipan Dey is a data scientist with a wide range of interests, covering topics such as machine learning, deep learning, image processing, and computer vision. He has worked in numerous data science fields, working with recommender systems, predictive models for the events industry, sensor localization models, sentiment analysis, and device prognostics. He earned his master's degree in computer science from the University of Maryland, Baltimore County, and has published in a few IEEE Data Mining conferences and journals. He has earned certifications from 100+ MOOCs on data science, machine learning, deep learning, image processing, and related courses. He is a regular blogger (sandipanweb) and is a machine learning education enthusiast.

作者簡介(中文翻譯)

Sandipan Dey 是一位資料科學家,對機器學習、深度學習、影像處理和電腦視覺等領域有廣泛的興趣。他在多個資料科學領域工作過,包括推薦系統、活動行業的預測模型、感測器定位模型、情感分析和設備預測等。他在馬里蘭大學巴爾的摩縣分校獲得了計算機科學碩士學位,並在幾個IEEE數據挖掘會議和期刊上發表過論文。他通過100多個MOOC課程獲得了資料科學、機器學習、深度學習、影像處理和相關課程的證書。他是一位常規博主(sandipanweb),也是一位機器學習教育愛好者。

目錄大綱

  1. Image Manipulation and Transformation
  2. Image Enhancement
  3. Image Restoration
  4. Binary Image Processing
  5. Image Registration
  6. Image Segmentation
  7. Image Classification
  8. Object Detection in Images
  9. Face Detection and Recognition

目錄大綱(中文翻譯)

圖像操作和轉換
圖像增強
圖像恢復
二值圖像處理
圖像配準
圖像分割
圖像分類
圖像中的物體檢測
人臉檢測和識別