【Basic】Image Contour Detection in MATLAB: Using Edge Detection and Contour Extraction

发布时间: 2024-09-15 02:44:14 阅读量: 72 订阅数: 63
ZIP

Table-Detection-Extraction:以某种形式检测表格并提取表格以及表格的单元格

# 2.1 Sobel Operator ### 2.1.1 Principle and Formula The Sobel operator is a first-order differential operator used for detecting edges in images. It works by calculating the gradient vector for each pixel in the image. The direction of the gradient vector points towards the direction of fastest brightness change in the image, while its magnitude represents the rate of that brightness change. The Sobel operator uses two 3x3 convolution kernels, one for horizontal and one for vertical gradient computation. The horizontal kernel is: ``` [-1 0 1] [-2 0 2] [-1 0 1] ``` And the vertical kernel is: ``` [-1 -2 -1] [0 0 0] [1 2 1] ``` For each pixel in the image, these two kernels are convolved with the local 3x3 region of the image to produce the horizontal and vertical gradient components. Together, these components make up the gradient vector. # 2. Edge Detection Techniques Edge detection is a fundamental technique in image processing, aiming to detect discontinuities between pixels in an image, thereby extracting edge information from the image. There are many edge detection algorithms, among which the Sobel operator, Canny operator, and Laplace operator are three commonly used edge detection operators. ### 2.1 Sobel Operator The Sobel operator is a first-order derivative edge detection operator that detects edges by calculating the amplitude of the pixel gradients in the image. It uses two convolution kernels to calculate the gradients in the horizontal and vertical directions: ```matlab % Horizontal Sobel Operator Gx = [-1 0 1; -2 0 2; -1 0 1]; % Vertical Sobel Operator Gy = [-1 -2 -1; 0 0 0; 1 2 1]; ``` The formula for the gradient magnitude of the Sobel operator is: ``` G = sqrt(Gx.^2 + Gy.^2) ``` ### 2.1.1 MATLAB Implementation In MATLAB, the `imgradientxy` function can be used to perform Sobel operator edge detection: ```matlab % Read image I = imread('image.jpg'); % Sobel Operator Edge Detection [Gx, Gy] = imgradientxy(I); G = sqrt(Gx.^2 + Gy.^2); % Display edge detection results imshow(G, []); ``` ### 2.2 Canny Operator The Canny operator is a multi-stage edge detection operator that detects edges through steps such as Gaussian smoothing, gradient computation, non-maximum suppression, and hysteresis thresholding. The Canny operator has good noise immunity and accurate edge localization. ### 2.2.1 Principle and Formula The principle and formula of the Canny operator are as follows: 1. **Gaussian Smoothing:** Use a Gaussian filter to smooth the image, removing noise. 2. **Gradient Computation:** Use the Sobel operator to calculate the gradient magnitude and direction of the image. 3. **Non-Maximum Suppression:** Suppress non-maximum gradient magnitudes along the gradient direction, keeping only local maxima. 4. **Hysteresis Thresholding:** Use two thresholds (high and low) to threshold the gradient magnitudes after non-maximum suppression. Pixels with gradient magnitudes higher than the high threshold are considered edge pixels, while those lower than the low threshold are considered non-edge pixels. Pixels between the high and low thresholds are judged based on the edge state of their neighboring pixels. ### 2.2.2 MATLAB Implementation In MATLAB, the `edge` function can be used to perform Canny operator edge detection: ```matlab % Read image I = imread('image.jpg'); % Canny Operator Edge Detection edges = edge(I, 'canny'); % Display edge detection results imshow(edges, []); ``` ### 2.3 Laplace Operator The Laplace operator is a second-order derivative edge detection operator that detects edges by calculating the second derivative of image pixels. The Laplace operator has good edge localization accuracy but poor noise immunity. ### 2.3.1 Principle and Formula The principle and formula of the Laplace operator are as follows: ``` L = ∇^2 I = ∂^2 I / ∂x^2 + ∂^2 I / ∂y^2 ``` Where: * L: Laplace operator * I: Image * ∇^2: Laplacian operator * ∂^2 I / ∂x^2: Second derivative of the image in the x direction * ∂^2 I / ∂y^2: Second derivative of the image in the y direction ### 2.3.2 MATLAB Implementation In MATLAB, the `laplacian` function can be used to perform Laplace operator edge detection: ```matlab % Read image I = imread('image.jpg'); % Laplace Operator Edge Detection L = laplacian(I); % Display edge detection results imshow(L, []); ``` # 3. Contour Extraction Algorithms ### 3.1 Boundary Tracking Algorithm #### 3.1.1 Principle and Steps The boundary tracking algorithm is a contour extraction algorithm based on pixel connectivity. Its basic principle is to trace along the edges of the image pixel by pixel until returning to the starting point. The specific steps are as follows: 1. **Initialization:** Select an edge pixel in the image as the starting point. 2. **Direction Determination:** Determine the direction with the largest gradient value among the eight neighboring pixels around the starting point. 3. **Movement:** Move to the next pixel in the direction with the largest gradient value. 4. **Judgment:** Determine if the current pixel is an edge pixel. If it is, continue moving; otherwise, return to the starting point. 5. **Repeat:** Repeat steps 2-4 until returning to the starting point. #### 3.1.2 MATLAB Implementation ```matlab function boundary = boundaryTracking(image) % Get the image gradient [Gx, Gy] = gra ```
corwn 最低0.47元/天 解锁专栏
买1年送3月
点击查看下一篇
profit 百万级 高质量VIP文章无限畅学
profit 千万级 优质资源任意下载
profit C知道 免费提问 ( 生成式Al产品 )

相关推荐

SW_孙维

开发技术专家
知名科技公司工程师,开发技术领域拥有丰富的工作经验和专业知识。曾负责设计和开发多个复杂的软件系统,涉及到大规模数据处理、分布式系统和高性能计算等方面。

专栏目录

最低0.47元/天 解锁专栏
买1年送3月
百万级 高质量VIP文章无限畅学
千万级 优质资源任意下载
C知道 免费提问 ( 生成式Al产品 )

最新推荐

ODU flex故障排查:G.7044标准下的终极诊断技巧

![ODU flex-G.7044-2017.pdf](https://img-blog.csdnimg.cn/img_convert/904c8415455fbf3f8e0a736022e91757.png) # 摘要 本文综述了ODU flex技术在故障排查方面的应用,重点介绍了G.7044标准的基础知识及其在ODU flex故障检测中的重要性。通过对G.7044协议理论基础的探讨,本论文阐述了该协议在故障诊断中的核心作用。同时,本文还探讨了故障检测的基本方法和高级技术,并结合实践案例分析,展示了如何综合应用各种故障检测技术解决实际问题。最后,本论文展望了故障排查技术的未来发展,强调了终

环形菜单案例分析

![2分钟教你实现环形/扇形菜单(基础版)](https://balsamiq.com/assets/learn/controls/dropdown-menus/State-open-disabled.png) # 摘要 环形菜单作为用户界面设计的一种创新形式,提供了不同于传统线性菜单的交互体验。本文从理论基础出发,详细介绍了环形菜单的类型、特性和交互逻辑。在实现技术章节,文章探讨了基于Web技术、原生移动应用以及跨平台框架的不同实现方法。设计实践章节则聚焦于设计流程、工具选择和案例分析,以及设计优化对用户体验的影响。测试与评估章节覆盖了测试方法、性能安全评估和用户反馈的分析。最后,本文展望

【性能优化关键】:掌握PID参数调整技巧,控制系统性能飞跃

![【性能优化关键】:掌握PID参数调整技巧,控制系统性能飞跃](https://ng1.17img.cn/bbsfiles/images/2023/05/202305161500376435_5330_3221506_3.jpg) # 摘要 本文深入探讨了PID控制理论及其在工业控制系统中的应用。首先,本文回顾了PID控制的基础理论,阐明了比例(P)、积分(I)和微分(D)三个参数的作用及重要性。接着,详细分析了PID参数调整的方法,包括传统经验和计算机辅助优化算法,并探讨了自适应PID控制策略。针对PID控制系统的性能分析,本文讨论了系统稳定性、响应性能及鲁棒性,并提出相应的提升策略。在

系统稳定性提升秘籍:中控BS架构考勤系统负载均衡策略

![系统稳定性提升秘籍:中控BS架构考勤系统负载均衡策略](https://img.zcool.cn/community/0134e55ebb6dd5a801214814a82ebb.jpg?x-oss-process=image/auto-orient,1/resize,m_lfit,w_1280,limit_1/sharpen,100) # 摘要 本文旨在探讨中控BS架构考勤系统中负载均衡的应用与实践。首先,介绍了负载均衡的理论基础,包括定义、分类、技术以及算法原理,强调其在系统稳定性中的重要性。接着,深入分析了负载均衡策略的选取、实施与优化,并提供了基于Nginx和HAProxy的实际

【Delphi实践攻略】:百分比进度条数据绑定与同步的终极指南

![要进行追迹的光线的综述-listview 百分比进度条(delphi版)](https://i0.hdslb.com/bfs/archive/e95917253e0c3157b4eb7594bdb24193f6912329.jpg) # 摘要 本文针对百分比进度条的设计原理及其在Delphi环境中的数据绑定技术进行了深入研究。首先介绍了百分比进度条的基本设计原理和应用,接着详细探讨了Delphi中数据绑定的概念、实现方法及高级应用。文章还分析了进度条同步机制的理论基础,讨论了实现进度条与数据源同步的方法以及同步更新的优化策略。此外,本文提供了关于百分比进度条样式自定义与功能扩展的指导,并

【TongWeb7集群部署实战】:打造高可用性解决方案的五大关键步骤

![【TongWeb7集群部署实战】:打造高可用性解决方案的五大关键步骤](https://user-images.githubusercontent.com/24566282/105161776-6cf1df00-5b1a-11eb-8f9b-38ae7c554976.png) # 摘要 本文深入探讨了高可用性解决方案的实施细节,首先对环境准备与配置进行了详细描述,涵盖硬件与网络配置、软件安装和集群节点配置。接着,重点介绍了TongWeb7集群核心组件的部署,包括集群服务配置、高可用性机制及监控与报警设置。在实际部署实践部分,本文提供了应用程序部署与测试、灾难恢复演练及持续集成与自动化部署

JY01A直流无刷IC全攻略:深入理解与高效应用

![JY01A直流无刷IC全攻略:深入理解与高效应用](https://www.electricaltechnology.org/wp-content/uploads/2016/05/Construction-Working-Principle-and-Operation-of-BLDC-Motor-Brushless-DC-Motor.png) # 摘要 本文详细介绍了JY01A直流无刷IC的设计、功能和应用。文章首先概述了直流无刷电机的工作原理及其关键参数,随后探讨了JY01A IC的功能特点以及与电机集成的应用。在实践操作方面,本文讲解了JY01A IC的硬件连接、编程控制,并通过具体

先锋SC-LX59:多房间音频同步设置与优化

![多房间音频同步](http://shzwe.com/static/upload/image/20220502/1651424218355356.jpg) # 摘要 本文旨在介绍先锋SC-LX59音频系统的特点、多房间音频同步的理论基础及其在实际应用中的设置和优化。首先,文章概述了音频同步技术的重要性及工作原理,并分析了影响音频同步的网络、格式和设备性能因素。随后,针对先锋SC-LX59音频系统,详细介绍了初始配置、同步调整步骤和高级同步选项。文章进一步探讨了音频系统性能监测和质量提升策略,包括音频格式优化和环境噪音处理。最后,通过案例分析和实战演练,展示了同步技术在多品牌兼容性和创新应用

【S参数实用手册】:理论到实践的完整转换指南

![【S参数实用手册】:理论到实践的完整转换指南](https://wiki.electrolab.fr/images/thumb/5/5c/Etalonnage_9.png/900px-Etalonnage_9.png) # 摘要 本文系统阐述了S参数的基础理论、测量技术、在射频电路中的应用、计算机辅助设计以及高级应用和未来发展趋势。第一章介绍了S参数的基本概念及其在射频工程中的重要性。第二章详细探讨了S参数测量的原理、实践操作以及数据处理方法。第三章分析了S参数在射频电路、滤波器和放大器设计中的具体应用。第四章进一步探讨了S参数在CAD软件中的集成应用、仿真优化以及数据管理。第五章介绍了

专栏目录

最低0.47元/天 解锁专栏
买1年送3月
百万级 高质量VIP文章无限畅学
千万级 优质资源任意下载
C知道 免费提问 ( 生成式Al产品 )