A method for detect and correcting bill direction and an automatic ticket checking system
A technology of direction detection and bills, applied in the direction of instruments, character and pattern recognition, computer parts, etc., to achieve the effect of high recognition accuracy, accurate results, and extended angle range
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Embodiment 1
[0046] see figure 1 In this embodiment, a bill direction detection and correction method is provided, which mainly involves a feature area clustering algorithm and a Radon transformation algorithm, and the specific steps are as follows:
[0047] Step 1: Perform grayscale processing on the collected bill image to obtain a grayscale image.
[0048] Usually, the relationship between white and black is divided into several levels according to the logarithmic relationship, which is called gray scale. It is called a grayscale image, which means that each pixel has only one sampled color on the image. Grayscale processing of any image is a very mature existing technology, so I won’t go into details here.
[0049] Step 2: Segment the grayscale image by using a feature region clustering algorithm, and highlight information regions on the bill by setting a grayscale threshold.
[0050] The information area is the face of the bill. For the highlighting and extraction of the information...
Embodiment 2
[0093] This embodiment 2 adopts the bill direction detection and correction method in embodiment 1, and carries out direction detection and correction to the train ticket image collected after tilting 120 degrees, in order to verify the feasibility and effect of the method described in embodiment 1, The specific process is as follows:
[0094] (1) Perform grayscale processing on the collected bill image to obtain a grayscale image, such as Figure 4 as shown in (A);
[0095] (2) Using the 3-means clustering algorithm to perform image segmentation on the grayscale image, that is, in the first step of the K-means clustering algorithm, 3 pixels are set as the initial center points of the clustering, so that the K-means clustering algorithm can be used Carry out 3-mean clustering on the train ticket image, so that all pixels on the train ticket image can be clustered into three gray levels, that is, in the collected train ticket image, the background of the ticket (that is, the b...
Embodiment 3
[0101] Present embodiment 3 adopts the method of embodiment 1 or embodiment 2, in plane Cartesian coordinate system, the train ticket image of 60 °, 120 °, 210 ° and 330 ° in four quadrants is carried out inclination angle test, and the result presented, respectively, as Figure 5 , Figure 6 , Figure 7 ,as well as Figure 8 As shown, it can be seen that the actual inclination angle of the train ticket image is highly consistent with the inclination angle of the monitored train ticket image. It can be seen that the bill direction detection and correction method provided by the present invention can be accurately for all angles (in the range of 0 to 360 degrees), Orientation detection for train ticket images in any orientation.
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