Method and device for detecting and processing dynamic image and display terminal
A technology of dynamic images and processing methods, applied in the field of image processing, can solve the problems of reduced recognition rate and increased data processing volume, and achieves the effects of improving the accuracy rate, eliminating interference, and reducing the amount of calculation.
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Embodiment 1
[0033] figure 1 The implementation flow of the dynamic image detection and processing method provided by Embodiment 1 of the present invention is shown, and the process of the method is described in detail as follows:
[0034] In step S101, an image frame containing a reference target is collected, and preprocessing is performed on the image frame.
[0035] In the embodiment of the present invention, the image acquisition process is as follows: the color camera collects a preset number (for example, 25) of color images per second, and each color image is numbered sequentially to obtain a sequence of color frames.
[0036] Because the acquired color image is often polluted by intensity random signal, namely noise. Image preprocessing can remove interfering noise. In this embodiment, a linear smoothing filter is used for image preprocessing. The linear filter uses the weighted sum of pixels in the continuous window function to achieve filtering. The formula is:
[0037] ...
Embodiment 2
[0058] figure 2 The processing flow of the dynamic image detection processing method provided by the second embodiment of the present invention is shown.
[0059] In step S201, an image frame including a reference target is collected, and preprocessing is performed on the image frame.
[0060] Wherein, the specific implementation process of step S201 is the same as that of step S101 in the above-mentioned embodiment 1. For details, refer to the above-mentioned embodiment, and details are not repeated here.
[0061] In step S202, obtain the edge profile of the reference target of the image frame, obtain the gradient direction of each edge point on the edge profile of the reference target, count the number of edge points on the gradient direction of each edge point, and calculate all The average value of the number of edge points in the edge point gradient direction.
[0062] In this embodiment, the feature value corresponding to the reference target is specifically the avera...
Embodiment 3
[0085] Figure 5 The processing flow of the dynamic image detection processing method provided by the third embodiment of the present invention is shown.
[0086] In step S301, an image frame containing a reference target is collected, and preprocessing is performed on the image frame.
[0087] Wherein, the specific implementation process of step S301 is the same as that of step S101 in the above-mentioned embodiment 1. For details, refer to the above-mentioned embodiment, which will not be repeated here.
[0088] In step S302, obtain the edge contour of the reference object of the image frame, traverse each edge point on the edge contour of the reference object, obtain the uppermost, lowermost, leftmost and rightmost edge points, and obtain the minimum circumscribed rectangle, according to the minimum circumscribed rectangle Rectangle Gets the width, height, and aspect ratio of the smallest bounding rectangle of the reference target.
[0089] In this embodiment, the feature...
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