通常在 OCR 的过程中,图像文件本质上是被切割成段,每个字符都被识别为一个段。例如,
必须转换为类似的东西
此外,是否有任何针对亚洲语言(如泰卢固语)的算法可用于此目的?如果没有,这对英语是怎么做的?
通常在 OCR 的过程中,图像文件本质上是被切割成段,每个字符都被识别为一个段。例如,
必须转换为类似的东西
此外,是否有任何针对亚洲语言(如泰卢固语)的算法可用于此目的?如果没有,这对英语是怎么做的?
使用 OpenCV 可以轻松完成。下面是一个示例代码:
import cv2
import numpy as np
# Load the image
img = cv2.imread('sof.png')
# convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# smooth the image to avoid noises
gray = cv2.medianBlur(gray,5)
# Apply adaptive threshold
thresh = cv2.adaptiveThreshold(gray,255,1,1,11,2)
thresh_color = cv2.cvtColor(thresh,cv2.COLOR_GRAY2BGR)
# apply some dilation and erosion to join the gaps
thresh = cv2.dilate(thresh,None,iterations = 3)
thresh = cv2.erode(thresh,None,iterations = 2)
# Find the contours
contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
# For each contour, find the bounding rectangle and draw it
for cnt in contours:
x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
cv2.rectangle(thresh_color,(x,y),(x+w,y+h),(0,255,0),2)
# Finally show the image
cv2.imshow('img',img)
cv2.imshow('res',thresh_color)
cv2.waitKey(0)
cv2.destroyAllWindows()
输出将如下所示: