基于matlab编写的图像识别(正方形、三角形、圆形)，包含缺陷图形

clc; clear; close all; % 读取图像 pic = imread('test.jpg'); % Make sure this points to the correct file path gray_pic = rgb2gray(pic); % 使用灰度图进行二值化 binary_img = 1 - imbinarize(gray_pic, 0.73); % 填充区域和删除小对象 fill_hole = imfill(binary_img, 'holes'); small_objects_removed = bwareaopen(fill_hole, 80); % 对比填充后和原始的二值图像，找出空洞和缺陷 defects_img = fill_hole - binary_img; % 提取边界和计算区域属性 [B, L] = bwboundaries(small_objects_removed, 'noholes'); out_result = regionprops(small_objects_removed, 'Extent', 'Centroid', 'BoundingBox', 'Perimeter', 'Area'); % 显示原始图像 figure; imshow(pic); title('圆形、三角形、正方形和长方形检测'); hold on; % 形状识别和显示 for i = 1:length(out_result) centroid = out_result(i).Centroid; bbox = out_result(i).BoundingBox; circularity = 4 * pi * out_result(i).Area / (out_result(i).Perimeter^2); % 检测是否有空洞或缺陷 defect_area = bwarea(defects_img(L == i)); if circularity > 0.8 if defect_area > 0 % 如果有空洞或缺陷 shape = '有缺陷的圆'; end else shape = '圆形'; end if out_result(i).Extent > 0.54 % 计算长宽比，来区分正方形和长方形 aspect_ratio = bbox(3) / bbox(4); if abs(aspect_ratio - 1) < 0.1 % 长宽比接近1则认为是正方形 shape = '正方形'; else shape = '长方形'; end else shape = '三角形'; end text(centroid(1)-40, centroid(2), shape, 'Color', 'w', 'FontSize', 12, 'FontWeight', 'bold'); end % 绘制边界 for j = 1:length(B) boundary = B{j}; plot(boundary(:, 2), boundary(:, 1), 'r', 'LineWidth', 2); end hold off;