段从嘈杂号牌每个字符(segment each character from noisy numbe

我做的，我已经发现我的号牌从车辆ANI在尼泊尔车牌检测项目倾斜号牌，但结果是号牌的噪声图像。

我想知道如何划分每个字符出来的，因此它可以检测部分被发送。我想这样做，但它只是分段的人物从第二行。

def segment(image):
    H = 100.
    height, width, depth = image.shape
    imgScale = H/height
    newX,newY = image.shape[1]*imgScale, image.shape[0]*imgScale
    image = cv2.resize(image,(int(newX),int(newY)))

    cv2.imshow("Show by CV2",image)
    cv2.waitKey(0)
    cv2.imwrite("resizeimg.jpg",image)

    idx =0 
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    _,thresh = cv2.threshold(gray,127,255,cv2.THRESH_TOZERO)

    cv2.imshow("thresh",thresh)
    cv2.waitKey(0)

    # gray=cv2.cvtColor(plate,cv2.COLOR_BW2GRAY)
    _,contours,_ = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
    for cnt in contours:
        idx += 1
        x,y,w,h = cv2.boundingRect(cnt)
        roi = image[y:y+h,x:x+w]
        if(w > 10 and h > 10):
            cv2.imwrite(str(idx) + '.jpg', roi)

假设有所述板的比率并且可以由y轴减半的板。从左至右，脱粒图像，图像morphologyEx，轮廓。应用与另一半一样。

image = cv2.imread("1.PNG")

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
_,thresh = cv2.threshold(gray,127,255,cv2.THRESH_TOZERO)
cv2.imshow("thresh",thresh)

element = cv2.getStructuringElement(shape=cv2.MORPH_RECT, ksize=(5, 11))

morph_img = thresh.copy()
cv2.morphologyEx(src=thresh, op=cv2.MORPH_CLOSE, kernel=element, dst=morph_img)
cv2.imshow("morph_img",morph_img)


_,contours,_ = cv2.findContours(morph_img,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
for c in contours:
    r = cv2.boundingRect(c)
    cv2.rectangle(image,(r[0],r[1]),(r[0]+r[2],r[1]+r[3]),(0,0,255),2)

cv2.imshow("img",image)

cv2.waitKey(0)
cv2.destroyAllWindows()

另一种方式来段中的字符是找到沿x轴和y轴的灰度值的总和。你可以很容易地看到有在x轴的3个峰分别是3个字符，并在y轴的峰值是在您的角色定位。