Realizing clock dial recognition based on Hough transform of MATLAB

Realizing clock dial recognition based on Hough transform of MATLAB

Clock dial recognition is an important application area in computer vision, where it can be used to automate tasks such as time measurement and clock calibration. This article will introduce how to use the Hough transform algorithm in MATLAB to realize the recognition of clock dials, and provide corresponding source code examples.

First, we need to clearly identify the target of the clock dial. Clock dials are usually circular or nearly circular in shape, so we can use the Hough transform to detect circular outlines. The Hough transform is a common technique for detecting shapes such as lines and circles in images by accumulating them in parameter space.

The following are the steps to use MATLAB to realize clock dial recognition:

Step 1: Read the image
First, we need to read the clock image to be processed. This can be achieved using MATLAB's imread function, for example:

image = imread('clock_image.jpg');

Step 2: Image preprocessing
Before performing Hough transformation, we need to preprocess the image to improve the accuracy of dial recognition. Commonly used preprocessing methods include grayscale, image smoothing and edge detection. Here's an example:

gray_image = rgb2gray(image);  % 将图像转换为灰度图像
smooth_image = imgaussfilt(gray_image, 2);  % 对灰度图像进行高斯平滑
edges = edge(smooth_image, 'Canny');  % 进行边缘检测

Step 3: Hough Transform
Next, we can use MATLAB's hough function to perform Hough transformation in order to detect the circular outline of the clock dial. Here's an example:

[accum, centers] = hough(edges, 'Theta', -90:0.5:8