500字范文 > Opencv机器视觉缺陷检测印刷检测

Opencv机器视觉缺陷检测印刷检测

时间：2022-12-14 22:06:52

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Opencv机器视觉缺陷检测印刷检测

Opencv机器视觉缺陷检测，印刷检测

用巴氏距离，surf特征点匹配检测Pyqt制作简单界面运行效果图surf特征点匹配巴氏距离直方图下载链接

用巴氏距离，surf特征点匹配检测

代码片段

#巴氏距离hist1 = create_hist(imgName) # 给标准样品绘制直方图for i in range(1, 2):print(i) # 打印图片序号img = cv2.imread(imgName1)hist2 = create_hist(imgName1) # 给测试样品绘制直方图match1 = pareHist(hist1, hist2, cv2.HISTCMP_BHATTACHARYYA) # 返回巴氏距离match2 = pareHist(hist1, hist2, cv2.HISTCMP_CORREL) # 返回相关性print("巴氏距离：%s, 相关性：%s" % (match1, match2))print("\n")if match2 >= 0.99999999999999:jpg = QtGui.QPixmap("hege.png").scaled(self.label_3.width(), self.label_3.height())self.label_3.setPixmap(jpg)else:jpg = QtGui.QPixmap("buhege.png").scaled(self.label_3.width(), self.label_3.height())self.label_3.setPixmap(jpg)print("\n")

#采用surf特征点集寻找图片缺陷std = cv2.imread(imgName1)test = cv2.imread(imgName)# 统一尺寸std = cv2.resize(std, (int(test.shape[1]), int(test.shape[0])))# 标准图透视变换成待测图角度std_wrap = rectify(test, std, is_debug=True)show = cv2.resize(std_wrap, (740, 580))cv2.imwrite("toushi.jpeg", show)#os.remove("toushi.jpeg")# 调整后的标准图与待测图作差diff = cv2.absdiff(test, std_wrap)diff = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)cv2.imwrite("diff.jpeg", diff)# 阈值化diff_thr = cv2.threshold(diff, 50, 255, cv2.THRESH_TOZERO)[1]cv2.imwrite("d_thr.jpeg", diff_thr)# 均值滤波diff_thr_blur = cv2.blur(diff_thr, (3, 3))cv2.imwrite("dt_blur.jpeg", diff_thr_blur)# 闭运算后阈值化kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))diff_thr_mor = cv2.morphologyEx(diff_thr, cv2.MORPH_CLOSE, kernel)cv2.imwrite("dtb_mor.jpeg", diff_thr_mor)# 标记缺陷dst = diff_thr_mor_, contours, hierarchy1 = cv2.findContours(dst, mode=cv2.RETR_TREE, method=cv2.CHAIN_APPROX_NONE)ex = test.copy()for c in contours:if len(c) < 10:continuex, y, w, h = cv2.boundingRect(c)cv2.rectangle(ex, (x, y), (x + w, y + h), (255, 255, 0), 2)ex = cv2.resize(ex, (640, 480))print(ex)cv2.imwrite("final.jpeg", ex)cv2.waitKey(0)compare(match2, img, i) # 比较并绘制