Learn from Scratch Signal and Image Processing with Python GUI

In this book, you will learn how to use OpenCV, NumPy library and other libraries to perform signal processing, image processing, object detection, and feature extraction with Python GUI (PyQt). You will learn how to filter signals, detect edges and segments, and denoise images with PyQt. You will also learn how to detect objects (face, eye, and mouth) using Haar Cascades and how to detect features on images using Harris Corner Detection, Shi-Tomasi Corner Detector, Scale-Invariant Feature Transform (SIFT), and Features from Accelerated Segment Test (FAST).In Chapter 1, you will learn: Tutorial Steps To Create A Simple GUI Application, Tutorial Steps to Use Radio Button, Tutorial Steps to Group Radio Buttons, Tutorial Steps to Use CheckBox Widget, Tutorial Steps to Use Two CheckBox Groups, Tutorial Steps to Understand Signals and Slots, Tutorial Steps to Convert Data Types, Tutorial Steps to Use Spin Box Widget, Tutorial Steps to Use ScrollBar and Slider, Tutorial Steps to Use List Widget, Tutorial Steps to Select Multiple List Items in One List Widget and Display It in Another List Widget, Tutorial Steps to Insert Item into List Widget, Tutorial Steps to Use Operations on Widget List, Tutorial Steps to Use Combo Box, Tutorial Steps to Use Calendar Widget and Date Edit, and Tutorial Steps to Use Table Widget.In Chapter 2, you will learn: Tutorial Steps To Create A Simple Line Graph, Tutorial Steps To Create A Simple Line Graph in Python GUI, Tutorial Steps To Create A Simple Line Graph in Python GUI: Part 2, Tutorial Steps To Create Two or More Graphs in the Same Axis, Tutorial Steps To Create Two Axes in One Canvas, Tutorial Steps To Use Two Widgets, Tutorial Steps To Use Two Widgets, Each of Which Has Two Axes, Tutorial Steps To Use Axes With Certain Opacity Levels, Tutorial Steps To Choose Line Color From Combo Box, Tutorial Steps To Calculate Fast Fourier Transform, Tutorial Steps To Create GUI For FFT, Tutorial Steps To Create GUI For FFT With Some Other Input Signals, Tutorial Steps To Create GUI For Noisy Signal, Tutorial Steps To Create GUI For Noisy Signal Filtering, and Tutorial Steps To Create GUI For Wav Signal Filtering.In Chapter 3, you will learn: Tutorial Steps To Convert RGB Image Into Grayscale, Tutorial Steps To Convert RGB Image Into YUV Image, Tutorial Steps To Convert RGB Image Into HSV Image, Tutorial Steps To Filter Image, Tutorial Steps To Display Image Histogram, Tutorial Steps To Display Filtered Image Histogram, Tutorial Steps To Filter Image With CheckBoxes, Tutorial Steps To Implement Image Thresholding, and Tutorial Steps To Implement Adaptive Image Thresholding.In Chapter 4, you will learn: Tutorial Steps To Generate And Display Noisy Image, Tutorial Steps To Implement Edge Detection On Image, Tutorial Steps To Implement Image Segmentation Using Multiple Thresholding and K-Means Algorithm, and Tutorial Steps To Implement Image Denoising.In Chapter 5, you will learn: Tutorial Steps To Detect Face, Eye, and Mouth Using Haar Cascades, Tutorial Steps To Detect Face Using Haar Cascades with PyQt, Tutorial Steps To Detect Eye, and Mouth Using Haar Cascades with PyQt, and Tutorial Steps To Extract Detected Objects.In Chapter 6, you will learn: Tutorial Steps To Detect Image Features Using Harris Corner Detection, Tutorial Steps To Detect Image Features Using Shi-Tomasi Corner Detection, Tutorial Steps To Detect Features Using Scale-Invariant Feature Transform (SIFT), and Tutorial Steps To Detect Features Using Features from Accelerated Segment Test (FAST).

在這本書中，您將學習如何使用OpenCV、NumPy庫和其他庫來進行信號處理、圖像處理、物體檢測和特徵提取，並使用Python GUI（PyQt）。您將學習如何使用PyQt過濾信號、檢測邊緣和區段，以及對圖像進行降噪。您還將學習如何使用Haar級聯檢測器檢測物體（臉部、眼睛和嘴巴），以及如何使用Harris角點檢測、Shi-Tomasi角點檢測、尺度不變特徵變換（SIFT）和快速加速段測試（FAST）在圖像上檢測特徵。

在第1章中，您將學習：創建簡單GUI應用程序的教程步驟，使用單選按鈕的教程步驟，對單選按鈕進行分組的教程步驟，使用複選框小工具的教程步驟，使用兩個複選框組的教程步驟，理解信號和插槽的教程步驟，數據類型轉換的教程步驟，使用旋轉框小工具的教程步驟，使用滾動條和滑塊的教程步驟，使用列表小工具的教程步驟，在一個列表小工具中選擇多個列表項並在另一個列表小工具中顯示的教程步驟，將項目插入列表小工具的教程步驟，使用小工具列表的操作的教程步驟，使用組合框的教程步驟，使用日曆小工具和日期編輯的教程步驟，以及使用表格小工具的教程步驟。

在第2章中，您將學習：創建簡單折線圖的教程步驟，使用Python GUI創建簡單折線圖的教程步驟，使用Python GUI創建簡單折線圖的教程步驟：第2部分，在同一個軸上創建兩個或更多圖形的教程步驟，在一個畫布中創建兩個軸的教程步驟，使用兩個小工具的教程步驟，使用兩個具有兩個軸的小工具的教程步驟，使用特定不透明度級別的軸的教程步驟，從組合框中選擇線條顏色的教程步驟，計算快速傅立葉變換的教程步驟，為FFT創建GUI的教程步驟，使用其他輸入信號為FFT創建GUI的教程步驟，為噪聲信號創建GUI的教程步驟，為噪聲信號濾波創建GUI的教程步驟。

在第3章中，您將學習：將RGB圖像轉換為灰度的教程步驟，將RGB圖像轉換為YUV圖像的教程步驟，將RGB圖像轉換為HSV圖像的教程步驟，過濾圖像的教程步驟，顯示圖像直方圖的教程步驟，顯示過濾後圖像直方圖的教程步驟，使用複選框過濾圖像的教程步驟，實現圖像閾值處理的教程步驟，實現自適應圖像閾值處理的教程步驟。

在第4章中，您將學習：生成並顯示噪聲圖像的教程步驟，對圖像進行邊緣檢測的教程步驟，使用多閾值和K-Means算法進行圖像分割的教程步驟，實現圖像降噪的教程步驟。

在第5章中，您將學習：使用Haar級聯檢測器檢測臉部、眼睛和嘴巴的教程步驟，使用Haar級聯檢測器和PyQt檢測臉部的教程步驟，使用Haar級聯檢測器和PyQt檢測眼睛和嘴巴的教程步驟，提取檢測到的物體的教程步驟。

在第6章中，您將學習：使用Harris角點檢測檢測圖像特徵的教程步驟，使用Shi-Tomasi角點檢測檢測圖像特徵的教程步驟，使用尺度不變特徵變換（SIFT）檢測特徵的教程步驟，使用快速加速段測試（FAST）檢測特徵的教程步驟。