Intelligent logistics turnover control system based on image processing

Abstract

The present invention relates to an intelligent logistics flip control system based on image processing, comprising: a flip execution device, which is used to perform flip processing on the current transmission object to achieve the conversion of the height of the current transmission object when the on-site resolution height corresponding to the current transmission object is greater than the maximum pass height of the front transmission environment; a feature mapping mechanism, which is used to perform real-time analysis of the height of the current transmission object based on a customized visual analysis mechanism. Through the present invention, the on-site height of the current transmission object entity obtained by customized visual analysis can be wirelessly transmitted to the flip execution device as the on-site resolution height corresponding to the current transmission object, and the flip execution device is used to perform flip processing on the current transmission object to achieve the conversion of the height of the current transmission object when the on-site resolution height corresponding to the current transmission object is greater than the maximum pass height of the front transmission environment, thereby realizing intelligent avoidance of the height restriction of the front transmission environment.

Description

Technical Field

[0001] The present invention relates to the field of smart logistics, and in particular to a smart logistics turnover control system based on image processing. Background Art

[0002] "Smart + Sharing" logistics integrates the two concepts of intelligence and sharing, promotes the mutual adaptation, coupling and coordination of the main functional links of the logistics system, and complements each other, and ultimately promotes efficient and intelligent logistics operation processes, highly shared logistics resources, and comprehensive transformation and upgrading of logistics functions. The constraints of the "smart + sharing" coupling of logistics enterprises can be divided into seven main categories, including the level of logistics intelligence, the level of logistics sharing, the coupling environment, the coupling mechanism, the coupling ability, the coupling willingness, and the characteristics of the enterprise, as well as 23 sub-categories. The internal driving factors, external driving factors, intermediary factors, and regulatory factors constitute the four major mechanisms and the interactive integration of various action paths, jointly promoting the "smart + sharing" coupling operation of logistics enterprises.

[0003] In the prior art, during the transmission process of each object to be transmitted in smart logistics, if the height of the front channel is limited, resulting in the height of the current object to be transmitted exceeding the height of the front channel, the current object to be transmitted needs to be transferred to other transmission channels. In fact, after comparing the two height values, the height and width of the current object to be transmitted can be converted through a flipping mode, and the converted current object to be transmitted can continue to be transmitted through the front channel. Obviously, there is a lack of corresponding solutions in the prior art. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides an intelligent logistics flipping control system based on image processing, which can wirelessly transmit the on-site height of the current transported object entity obtained by customized visual analysis as the on-site resolution height corresponding to the current transported object to a flipping execution device. The flipping execution device is used to perform flipping processing on the current transported object to achieve the conversion of the height of the current transported object when the on-site resolution height corresponding to the current transported object is greater than the maximum pass height of the front transport environment, thereby realizing intelligent avoidance of the height restriction of the front transport environment and improving the transmission efficiency of the object entity.

[0005] According to the present invention, a smart logistics overturning control system based on image processing is provided, the system comprising:

[0006] A flip execution device, used for performing a flipping process on the current transport object to achieve a conversion of the height of the current transport object when the on-site resolution height corresponding to the current transport object is greater than the maximum pass height of the front transport environment;

[0007] A side acquisition device is located in front of the flip actuator and is arranged on the side of the conveying actuator that performs the object conveying operation so as to face the acquisition station of the conveying actuator, and is used to perform real-time image signal acquisition of the conveying environment of the current conveying object when the current conveying object arrives at the acquisition station, so as to obtain and output a corresponding side acquisition image;

[0008] A maximum filtering device, connected to the side acquisition device, for performing maximum filtering processing on the received side acquisition image to obtain and output a corresponding maximum filtering image;

[0009] A data sharpening device, connected to the maximum filtering device, for performing a spatial differential sharpening process on the received maximum filtering image to obtain and output a corresponding data sharpened image;

[0010] a content enhancement device, connected to the data sharpening device, for performing image content enhancement processing based on logarithmic transformation on the received data sharpened image, so as to obtain and output a corresponding content enhanced image;

[0011] A feature mapping mechanism connected to the content enhancement device, used to receive the content enhancement image, detect each pixel column of the current transmission object distributed in the content enhancement image based on the grayscale imaging characteristics corresponding to the current transmission object, analyze the difference between the vertical coordinate value of the pixel at the highest position and the vertical coordinate value of the pixel at the lowest position of each pixel column as its corresponding visual height, use the maximum value of each visual height corresponding to each pixel column of the current transmission object distributed in the content enhancement image as a reference value, and map the on-site height of the current transmission object entity according to the reference value and the acquisition focal length of the content enhancement image, the smaller the reference value, the lower the on-site height of the current transmission object entity obtained by mapping, and the closer the acquisition focal length of the content enhancement image, the lower the on-site height of the current transmission object entity obtained by mapping;

[0012] The wireless transceiver mechanism is electrically connected to the feature mapping mechanism and wirelessly connected to the flip execution device, and is used to wirelessly transmit the on-site height of the current transported object entity as the on-site resolution height corresponding to the current transported object to the flip execution device.

[0013] It can be seen that the present invention has at least the following main inventive concepts:

[0014] Inventive concept A: Based on the grayscale imaging characteristics corresponding to the current transmission object, each pixel column of the current transmission object distributed in the content enhancement image is detected, and for each pixel column, the difference between the vertical coordinate value of the pixel at the highest position and the vertical coordinate value of the pixel at the lowest position is analyzed as its corresponding visual height, and the maximum value of each visual height corresponding to each pixel column of the current transmission object distributed in the content enhancement image is used as a reference value, thereby achieving targeted analysis of the visual height of the current transmission object;

[0015] Inventive concept B: mapping the scene height of the current transported object entity according to the reference value and the acquisition focal length of the content-enhanced image, wherein the smaller the reference value, the lower the scene height of the current transported object entity obtained by mapping, and the closer the acquisition focal length of the content-enhanced image, the lower the scene height of the current transported object entity obtained by mapping;

[0016] Inventive concept C: The on-site height of the current transport object entity is wirelessly transmitted to the flipping execution device as the on-site resolution height corresponding to the current transport object. The flipping execution device is used to perform a flipping process on the current transport object to achieve the conversion of the height of the current transport object when the on-site resolution height corresponding to the current transport object is greater than the maximum pass height of the front transport environment, thereby realizing intelligent avoidance of the height restriction of the front transport environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0018] Figure 1 It is a structural block diagram of an intelligent logistics overturning control system based on image processing according to the primary embodiment of the present invention.

[0019] Figure 2 It is a structural block diagram of an intelligent logistics overturning control system based on image processing according to a secondary embodiment of the present invention.

[0020] Figure 3 The present invention is a structural block diagram of an intelligent logistics overturning control system based on image processing according to another embodiment of the present invention. DETAILED DESCRIPTION

[0021] The following will describe in detail an embodiment of the intelligent logistics reversal control system based on image processing of the present invention with reference to the accompanying drawings.

[0022] Figure 1 The structure block diagram of the intelligent logistics turnover control system based on image processing according to the primary embodiment of the present invention is shown, and the system includes:

[0023] A flip execution device, used for performing a flipping process on the current transport object to achieve a conversion of the height of the current transport object when the on-site resolution height corresponding to the current transport object is greater than the maximum pass height of the front transport environment;

[0024] For example, the flip execution device is used to perform a flipping process on the current conveying object to achieve the conversion of the height of the current conveying object when the on-site resolution height corresponding to the current conveying object is greater than the maximum pass height of the front conveying environment, including: the flip execution device has a built-in flip driving motor, which is used to perform a flipping process on the current conveying object;

[0025] A side acquisition device is located in front of the flip actuator and is arranged on the side of the conveying actuator that performs the object conveying operation so as to face the acquisition station of the conveying actuator, and is used to perform real-time image signal acquisition of the conveying environment of the current conveying object when the current conveying object arrives at the acquisition station, so as to obtain and output a corresponding side acquisition image;

[0026] A maximum filtering device, connected to the side acquisition device, for performing maximum filtering processing on the received side acquisition image to obtain and output a corresponding maximum filtering image;

[0027] A data sharpening device, connected to the maximum filtering device, for performing a spatial differential sharpening process on the received maximum filtering image to obtain and output a corresponding data sharpened image;

[0028] a content enhancement device, connected to the data sharpening device, for performing image content enhancement processing based on logarithmic transformation on the received data sharpened image, so as to obtain and output a corresponding content enhanced image;

[0029] A feature mapping mechanism connected to the content enhancement device, used to receive the content enhancement image, detect each pixel column of the current transmission object distributed in the content enhancement image based on the grayscale imaging characteristics corresponding to the current transmission object, analyze the difference between the vertical coordinate value of the pixel at the highest position and the vertical coordinate value of the pixel at the lowest position of each pixel column as its corresponding visual height, use the maximum value of each visual height corresponding to each pixel column of the current transmission object distributed in the content enhancement image as a reference value, and map the on-site height of the current transmission object entity according to the reference value and the acquisition focal length of the content enhancement image, the smaller the reference value, the lower the on-site height of the current transmission object entity obtained by mapping, and the closer the acquisition focal length of the content enhancement image, the lower the on-site height of the current transmission object entity obtained by mapping;

[0030] A wireless transceiver mechanism, electrically connected to the feature mapping mechanism and wirelessly connected to the flip execution device, for wirelessly transmitting the on-site height of the current transported object entity as the on-site resolution height corresponding to the current transported object to the flip execution device;

[0031] Among them, mapping the on-site height of the current transported object entity according to the reference value and the acquisition focal length of the content enhanced image, the smaller the reference value is, the lower the on-site height of the current transported object entity obtained by mapping, and the closer the acquisition focal length of the content enhanced image is, the lower the on-site height of the current transported object entity obtained by mapping includes: using a numerical mapping formula to represent the data mapping process of mapping the on-site height of the current transported object entity according to the reference value and the acquisition focal length of the content enhanced image.

[0032] Figure 2 It is a structural block diagram of an intelligent logistics overturning control system based on image processing according to a secondary embodiment of the present invention.

[0033] Compared to Figure 1 , Figure 2 The intelligent logistics turnover control system based on image processing can also include:

[0034] a current detection device, arranged near the maximum value filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism and connected to the maximum value filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively;

[0035] Among them, the current detection device is arranged near the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism and is respectively connected to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism, including: the current detection device is used to respectively realize the on-site measurement of the current of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism.

[0036] Figure 3 The present invention is a structural block diagram of an intelligent logistics overturning control system based on image processing according to another embodiment of the present invention.

[0037] Compared to Figure 1 , Figure 3 The intelligent logistics turnover control system based on image processing can also include:

[0038] a humidity detection device, arranged near the maximum value filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism and connected to the maximum value filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively;

[0039] Among them, the humidity detection device is arranged near the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism and is respectively connected to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism, including: the humidity detection device is used to respectively realize on-site measurement of the current humidity of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism.

[0040] Next, the specific structure of the intelligent logistics overturning control system based on image processing of the present invention is further described.

[0041] In the intelligent logistics reversal control system based on image processing according to various embodiments of the present invention:

[0042] An FPGA is used to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

[0043] In the intelligent logistics reversal control system based on image processing according to various embodiments of the present invention:

[0044] Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing guided filtering processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

[0045] In the intelligent logistics overturning control system based on image processing according to various embodiments of the present invention:

[0046] Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing box filtering processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

[0047] In the intelligent logistics overturning control system based on image processing according to various embodiments of the present invention:

[0048] Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing wavelet filtering processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

[0049] In the intelligent logistics overturning control system based on image processing according to various embodiments of the present invention:

[0050] Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing bilinear interpolation processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

[0051] In addition, in the intelligent logistics turnover control system based on image processing, a numerical mapping formula is used to represent the data mapping process of mapping the on-site height of the current transported object entity according to the reference value and the acquisition focal length of the content-enhanced image, including: in the numerical mapping formula, the reference value and the acquisition focal length of the content-enhanced image are used as two input contents of the numerical mapping formula, and the mapped on-site height of the current transported object entity is used as a single output content of the numerical mapping formula.

[0052] The intelligent logistics flipping control system based on image processing of the present invention is used to address the technical problem in the prior art that the object transmission efficiency is low due to the inability to perform channel transmission due to height restrictions. The on-site height of the current transmitted object entity obtained by customized visual analysis is wirelessly transmitted to the flipping execution device as the on-site resolution height corresponding to the current transmitted object. The flipping execution device is used to perform flipping processing on the current transmitted object to achieve the conversion of the height of the current transmitted object when the on-site resolution height corresponding to the current transmitted object is greater than the maximum pass height of the front transmission environment, thereby realizing intelligent avoidance of the height restriction of the front transmission environment.

[0053] Although the present invention has been described in conjunction with specific embodiments of the present invention, it is obvious to those skilled in the art that various modifications and variations can be made to the present invention without departing from the scope and spirit of the present invention. Therefore, it should be understood that the above embodiments are not restrictive in all aspects, but illustrative.

Claims

1. An intelligent logistics turnover control system based on image processing, characterized in that: The system comprises: A flip execution device, used for performing a flipping process on the current transport object to achieve a conversion of the height of the current transport object when the on-site resolution height corresponding to the current transport object is greater than the maximum pass height of the front transport environment; A side acquisition device is located in front of the flip actuator and is arranged on the side of the conveying actuator that performs the object conveying operation so as to face the acquisition station of the conveying actuator, and is used to perform real-time image signal acquisition of the conveying environment of the current conveying object when the current conveying object arrives at the acquisition station, so as to obtain and output a corresponding side acquisition image; A maximum filtering device, connected to the side acquisition device, for performing maximum filtering processing on the received side acquisition image to obtain and output a corresponding maximum filtering image; A data sharpening device, connected to the maximum filtering device, for performing a spatial differential sharpening process on the received maximum filtering image to obtain and output a corresponding data sharpened image; a content enhancement device, connected to the data sharpening device, for performing image content enhancement processing based on logarithmic transformation on the received data sharpened image, so as to obtain and output a corresponding content enhanced image; A feature mapping mechanism connected to the content enhancement device, used to receive the content enhancement image, detect each pixel column of the current transmission object distributed in the content enhancement image based on the grayscale imaging characteristics corresponding to the current transmission object, analyze the difference between the vertical coordinate value of the pixel at the highest position and the vertical coordinate value of the pixel at the lowest position of each pixel column as its corresponding visual height, use the maximum value of each visual height corresponding to each pixel column of the current transmission object distributed in the content enhancement image as a reference value, and map the on-site height of the current transmission object entity according to the reference value and the acquisition focal length of the content enhancement image, the smaller the reference value, the lower the on-site height of the current transmission object entity obtained by mapping, and the closer the acquisition focal length of the content enhancement image, the lower the on-site height of the current transmission object entity obtained by mapping; A wireless transceiver mechanism, electrically connected to the feature mapping mechanism and wirelessly connected to the flip execution device, for wirelessly transmitting the on-site height of the current transported object entity as the on-site resolution height corresponding to the current transported object to the flip execution device; The method includes: using a numerical mapping formula to represent a data mapping process of mapping the on-site height of the current transmission object entity according to the reference value and the acquisition focal length of the content-enhanced image; and mapping the on-site height of the current transmission object entity according to the reference value and the acquisition focal length of the content-enhanced image. a humidity detection device, arranged near the maximum value filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism and connected to the maximum value filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively; Wherein, the humidity detection device is used to respectively realize on-site measurement of the current humidity of the maximum value filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism.

2. The intelligent logistics turnover control system based on image processing as claimed in claim 1, characterized in that: FPGA is used to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

3. The intelligent logistics turnover control system based on image processing as claimed in claim 2, characterized in that: Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing guided filtering processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

4. The intelligent logistics turnover control system based on image processing as claimed in claim 2, characterized in that: Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing box filtering processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

5. The intelligent logistics turnover control system based on image processing as claimed in claim 2, characterized in that: Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing wavelet filtering processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

6. The intelligent logistics turnover control system based on image processing as claimed in claim 2, characterized in that: Using FPGA to perform image data processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively includes: performing bilinear interpolation processing on the output data of the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism to obtain the output processing data corresponding to the maximum filtering device, the data sharpening device, the content enhancement device and the feature mapping mechanism respectively.

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