毕业设计 python opencv实现车牌识别 颜色判断
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主要代码参考https://blog.csdn.net/wzh191920/article/details/79589506
GitHub:https://github.com/yinghualuowu
答辩通过了,补完~
该部分代码还包括缩小边界
def img_color(card_imgs): colors = [] for card_index, card_img in enumerate(card_imgs): green = yello = blue = black = white = 0 card_img_hsv = cv2.cvtColor(card_img, cv2.COLOR_BGR2HSV) # 有转换失败的可能,原因来自于上面矫正矩形出错 if card_img_hsv is None: continue row_num, col_num = card_img_hsv.shape[:2] card_img_count = row_num * col_num for i in range(row_num): for j in range(col_num): H = card_img_hsv.item(i, j, 0) S = card_img_hsv.item(i, j, 1) V = card_img_hsv.item(i, j, 2) if 11 < H <= 34 and S > 34: yello += 1 elif 35 < H <= 99 and S > 34: green += 1 elif 99 < H <= 124 and S > 34: blue += 1 if 0 < H < 180 and 0 < S < 255 and 0 < V < 46: black += 1 elif 0 < H < 180 and 0 < S < 43 and 221 < V < 225: white += 1 color = "no" limit1 = limit2 = 0 if yello * 2 >= card_img_count: color = "yello" limit1 = 11 limit2 = 34 # 有的图片有色偏偏绿 elif green * 2 >= card_img_count: color = "green" limit1 = 35 limit2 = 99 elif blue * 2 >= card_img_count: color = "blue" limit1 = 100 limit2 = 124 # 有的图片有色偏偏紫 elif black + white >= card_img_count * 0.7: color = "bw" colors.append(color) card_imgs[card_index] = card_img if limit1 == 0: continue xl, xr, yh, yl = accurate_place(card_img_hsv, limit1, limit2, color) if yl == yh and xl == xr: continue need_accurate = False if yl >= yh: yl = 0 yh = row_num need_accurate = True if xl >= xr: xl = 0 xr = col_num need_accurate = True if color =="green": card_imgs[card_index] = card_img else: card_imgs[card_index] = card_img[yl:yh, xl:xr] if color != "green" or yl < (yh - yl) // 4 else card_img[ yl - ( yh - yl) // 4:yh, xl:xr] if need_accurate: card_img = card_imgs[card_index] card_img_hsv = cv2.cvtColor(card_img, cv2.COLOR_BGR2HSV) xl, xr, yh, yl = accurate_place(card_img_hsv, limit1, limit2, color) if yl == yh and xl == xr: continue if yl >= yh: yl = 0 yh = row_num if xl >= xr: xl = 0 xr = col_num if color =="green": card_imgs[card_index] = card_img else: card_imgs[card_index] = card_img[yl:yh, xl:xr] if color != "green" or yl < (yh - yl) // 4 else card_img[ yl - ( yh - yl) // 4:yh, xl:xr] return colors,card_imgs
accrate_place部分
def accurate_place(card_img_hsv, limit1, limit2, color): row_num, col_num = card_img_hsv.shape[:2] xl = col_num xr = 0 yh = 0 yl = row_num row_num_limit = 21 col_num_limit = col_num * 0.8 if color != "green" else col_num * 0.5 # 绿色有渐变 for i in range(row_num): count = 0 for j in range(col_num): H = card_img_hsv.item(i, j, 0) S = card_img_hsv.item(i, j, 1) V = card_img_hsv.item(i, j, 2) if limit1 < H <= limit2 and 34 < S and 46 < V: count += 1 if count > col_num_limit: if yl > i: yl = i if yh < i: yh = i for j in range(col_num): count = 0 for i in range(row_num): H = card_img_hsv.item(i, j, 0) S = card_img_hsv.item(i, j, 1) V = card_img_hsv.item(i, j, 2) if limit1 < H <= limit2 and 34 < S and 46 < V: count += 1 if count > row_num - row_num_limit: if xl > j: xl = j if xr < j: xr = j return xl, xr, yh, yl
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