预处理褪色图像

Question

我正在尝试预处理稍微倾斜和褪色的收据图像。

我找到了调整照片位置的代码。但我不知道如何使文本清晰。

import cv2
import pytesseract
import numpy as np



img_path = "rec.jpg"

img = cv2.imread(img_path)
cv2.imshow("org",img)

img_rgb = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
cv2.imshow("rgb",img_rgb)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = 255 - gray
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Compute rotated bounding box
coords = np.column_stack(np.where(thresh > 0))
angle = cv2.minAreaRect(coords)[-1]

if angle < -45:
    angle = -(90 + angle)
else:
    angle = -angle
print(angle)

# Rotate image to deskew
(h, w) = img.shape[:2]
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, angle, 1.0)[enter image description here]
rotated = cv2.warpAffine(img, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)

cv2.imshow('thresh', thresh)
cv2.imshow('rotated', rotated)

bit_img = cv2.bitwise_not(rotated)

kernel = np.ones((2,2),np.uint8)

dilate_img = cv2.dilate(bit_img,kernel,iterations=1)

cv2.imshow("last",dilate_img)




cv2.waitKey(0)

尽管我用opencv尝试了各种代码，但准确率没有达到我想要的水平。

Answer 1

import cv2
import numpy as np

img_path = "rec.jpg"
img = cv2.imread(img_path)

# Convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Contrast enhancement using Adaptive Histogram Equalization
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
cl1 = clahe.apply(gray)

# Bilateral filtering
filtered = cv2.bilateralFilter(cl1, 9, 75, 75)

# Sharpening
kernel_sharpening = np.array([[-1, -1, -1],
                              [-1, 9, -1],
                              [-1, -1, -1]])
sharpened = cv2.filter2D(filtered, -1, kernel_sharpening)

# Adaptive thresholding
thresh = cv2.adaptiveThreshold(sharpened, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, 
                               cv2.THRESH_BINARY, 11, 2)

cv2.imshow('Processed Image', thresh)
cv2.waitKey(0)
cv2.destroyAllWindows()