Bank card number recognition method based on OpenCV
A recognition method, bank card number technology, applied in character recognition, character and pattern recognition, instruments, etc., can solve the problem of low accuracy of card number recognition, achieve the effect of improving accuracy, avoiding interference, and ensuring recognition speed
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Embodiment 1
[0047] Example 1: Bank card number recognition under strong light conditions.
[0048] refer to figure 1 , a bank card number recognition method based on OpenCV, comprising the following steps:
[0049] Step 1) Preprocessing the bank card image:
[0050] Step 1a) utilize the cvtColor function of OpenCV to carry out gray-scale processing to the color bank card image stored in advance, obtain as follows figure 2The grayscale image shown, from figure 2 It can be seen that the gray level of each pixel in the grayscale image is stored with an 8-bit binary number, so the gray level of each pixel ranges from 0 to 255, and there are 256 gray levels in total. It can reduce the storage space of the image and facilitate the subsequent image processing;
[0051] Step 1b) Judging the uniformity of the illumination intensity of the grayscale image:
[0052] Divide the gray level into three levels of high, medium and low, and calculate the ratio of the pixel points in the left and rig...
Embodiment 2
[0071] Example 2: Bank card number recognition under medium light conditions.
[0072] The other steps of this embodiment are the same as those of Embodiment 1, only step 1) has been adjusted.
[0073] Step 1) Preprocessing the bank card image:
[0074] Step 1a) Use the cvtColor function of OpenCV to grayscale the pre-stored color bank card image to obtain a grayscale image such as Figure 10 shown, from Figure 10 It can be seen that the gray level of each pixel in the grayscale image is stored with an 8-bit binary number, so the gray level of each pixel ranges from 0 to 255, and there are 256 gray levels in total. The storage space of the image can be reduced, and it is beneficial to the subsequent image processing; at the same time, the Figure 10 and figure 2 It can be seen from the comparison that the gray level of the grayscale image under medium light conditions is generally lower than that under strong light conditions, and the visual effect presented is darker; ...
Embodiment 3
[0080] Embodiment 3: Bank card number recognition under weak light conditions.
[0081] The other steps of this embodiment are the same as those of Embodiment 1, only step 1) has been adjusted.
[0082] Step 1) Preprocessing the bank card image:
[0083] Step 1a) Use the cvtColor function of OpenCV to grayscale the pre-stored color bank card image to obtain a grayscale image such as Figure 12 shown, from Figure 12 It can be seen that the gray level of each pixel in the grayscale image is stored with an 8-bit binary number, so the gray level of each pixel ranges from 0 to 255, and there are 256 gray levels in total. It can reduce the storage space of the image, and is beneficial to the subsequent image processing, and at the same time Figure 12 and Figure 10 It can be seen from the comparison that the gray level of the grayscale image under low light conditions is generally lower than that under medium light conditions, and the visual effect presented is darker;
[0084]...
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