Combined light perspective based visual recognition detection method of stems and stem ratios in leaves
A detection method and visual recognition technology, applied in the direction of character and pattern recognition, image data processing, instruments, etc., can solve the problems of not being able to satisfy the real-time control of production dynamics, destroying the shape of tobacco leaves, and losing the original value of tobacco leaves, etc. , to achieve easy engineering implementation and popularization and application, reduce the impact of detection results, and overcome the effect of long detection cycle
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Embodiment 1
[0043] The present invention uses a tobacco leaf and stem detection and sorting device to carry out a method for visual recognition and detection of stems in leaves based on transmitted light. image 3 An example of detection of stalk content in leaves of threshing and re-roasting production line. Proceed as follows:
[0044] The first step, sampling and fully diluted. Firstly, a 3 kg leaf threshing sample is taken online from the leaf threshing and re-roasting production line through the sampling device. One of the implementation methods of the sampling device is a combination of mechanical grabbing (or funnel) and weighing. The thinning system is mainly composed of vibrating plate, seven-star roller, high-speed belt conveyor, flat sorting pipeline and recycling channel, etc. The principle and process of dilution are described as follows:
[0045] 1) 3 kg of sampled tobacco leaves are first conveyed to the seven-star rollers through the vibrating disc, and the gap between ...
Embodiment 2
[0064] The light source in step 2 in Example 1 is replaced by a near-infrared light source with a wavelength of 920nm and a power of 100W surface light source. The example of backlight transmission to obtain the tobacco leaf image is as follows: Figure 6 (a), (b) and (c), the slender area with darker color in the figure is the tobacco stem. It can be seen from the figure that the blade and the tobacco stem area can be clearly distinguished by using the near-infrared light source, and the corresponding identification Test results such as Figure 6 (d), (e) and (f), the white area in the figure represents the identified tobacco stem area, and the results show that the near-infrared light source can better obtain clear perspective images of tobacco leaves and stems. Figure 6 (c) The middle part of the upper and lower tobacco stems is the overlapping area of leaves. From the results, when the leaves do not cover the next layer of tobacco stems, the upper and lower tobacco stem...
Embodiment 3
[0066] Considering that the tobacco leaves have more overlapping adaptability, the light source of this example chooses a light source with high penetrating power such as a soft X-ray light source, and other steps are similar to the first embodiment. Examples of tobacco leaf images and tobacco stem detection and recognition results obtained in the experiment Figure 7 shown. Figure 7 (a) is a photo of the real object. The tobacco stems in the area indicated by the red frame in the figure are completely wrapped by tobacco leaves, and the blue frame is covered by multiple tobacco leaves (more than 5 pieces). Figure 7 (b) is the obtained soft X-ray fluoroscopy image, Figure 7 (c) is the result of extraction of tobacco stems after treatment. From Figure 7 (b) It can be seen that the tobacco stem (slender white area) is very clear and easy to identify, whether it is wrapped by tobacco leaves or covered by multiple tobacco leaves, Figure 7 The recognition results of (c) als...
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