车牌字符分割python opencv

时间:2018-06-06 05:49:49

标签: python opencv image-processing ocr image-segmentation

我想隔离下图中的每个字符: enter image description here

它应该在每个角色周围创建一个矩形边界框。我的代码是创建一个圆形边界框。我需要将这些孤立的角色图像提供给我训练过的模型来预测角色。我还没有完成图像处理,之后我才提出这样的问题。

这是我正在使用的代码:

# Standard imports
import cv2
import numpy as np;

from PIL import Image
params = cv2.SimpleBlobDetector_Params()

# Change thresholds
params.minThreshold = 10;
params.maxThreshold = 200;

#Filter by Color

params.filterByColor=False
params.blobColor=255

# Filter by Area.
params.filterByArea = False
params.minArea = 50

# Filter by Circularity
params.filterByCircularity = False
params.minCircularity = 0.0785
#
# # Filter by Convexity
params.filterByConvexity = False
params.minConvexity = 0.87
#
# # Filter by Inertia
params.filterByInertia = False
params.minInertiaRatio = 0.01
# Read image
    im = cv2.imread("C:\\xx\\testimages\\bw_plate.jpg", cv2.IMREAD_GRAYSCALE)

cv2.threshold(im,200,255,cv2.THRESH_BINARY_INV,im)


# Set up the detector with default parameters.
detector = cv2.SimpleBlobDetector_create(params)

# Detect blobs.
keypoints = detector.detect(im)


# Draw detected blobs as red circles.
# cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures the size of the circle corresponds to the size of blob
im_with_keypoints = cv2.drawKeypoints(im, keypoints, np.array([]), (0, 0, 255),
                                      cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)

# Show keypoints
cv2.imshow("Keypoints", im_with_keypoints)
cv2.waitKey(0)

我的输出与以下代码是: enter image description here

为什么没有正确检测到0和2?另外,我如何为每个孤立的角色创建单独的jpeg文件?

我的项目的C ++实现使用CblobResult类进行分段。在python中有任何等效的库吗?

这是分段后每个字符的最终输出必须是这样的: enter image description here

1 个答案:

答案 0 :(得分:5)

删除背景噪音后,您可以输入如下图像:

然后,您可以使用以下代码获得所需内容:

import cv2
img = cv2.imread('test4.jpg', 0)
cv2.threshold(img,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU,img)
image, contours, hier = cv2.findContours(img, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
contours = sorted(contours, key=lambda ctr: cv2.boundingRect(ctr)[0])
cv2.imshow("contours", img)
cv2.waitKey(0)
d=0
for ctr in contours:
    # Get bounding box
    x, y, w, h = cv2.boundingRect(ctr)
    # Getting ROI
    roi = image[y:y+h, x:x+w]

    cv2.imshow('character: %d'%d,roi)
    cv2.imwrite('character_%d.png'%d, roi)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    d+=1