CN117726923B - Image communication system based on specific model - Google Patents
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- 238000003709 image segmentation Methods 0.000 claims abstract description 38
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- 239000011159 matrix material Substances 0.000 claims description 39
- 238000013500 data storage Methods 0.000 claims description 25
- 238000010191 image analysis Methods 0.000 claims description 15
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Abstract
One or more embodiments of the present specification provide an image communication system based on a specific model, including an image processing component and an image segmentation module, and an image receiving component for receiving an image; the image processing component acquires an image through the camera, stores and identifies the image, marks the image after the identification, and analyzes pixel data of the marked image; the image segmentation module is used for segmenting the marked image, acquiring corresponding colors of the segmented target image, separating the color image to obtain a gray image and color data of corresponding pixel points, and transmitting the gray image and the color data of the corresponding pixel points to the image receiving assembly through the data transmission module; the two groups of data of the RGB data and the gray image data are respectively transmitted, so that the accuracy of the image data is effectively ensured, and the problems that pixels are lost or the data volume is large in the transmission process in the conventional image communication mode are avoided.
Description
Technical Field
One or more embodiments of the present disclosure relate to the field of image communication systems, and more particularly, to an image communication system based on a specific model.
Background
Image communication is communication that transmits and receives image signals or what is called image information. Unlike widely used voice communication, not only voice but also visual information such as images, characters, charts and the like are transmitted, and the visual information is converted into electric signals by an image communication device to be transmitted, and then the electric signals are actually reproduced at a receiving end. The image communication can be said to be communication using visual information, or it is called communication of visual information.
Application number in prior art: 2010800466247, patent name: an image transmission device and an image communication system are described in chinese patent application "measurement of information on a busy state of a communication channel used for wireless communication" and determination of the state of the communication channel based on the measurement result. Therefore, even if the data signals of adjacent communication channels generate interference, the state of the communication channels can be detected more accurately, however, the mode is that the data volume is not changed in the image communication process, and the integrity of the image is not accurately judged after the image is received, so that the prior art cannot be satisfied.
Disclosure of Invention
In view of this, an object of one or more embodiments of the present disclosure is to provide an image communication system based on a specific model, so as to solve the problems of imperfect image communication, inaccurate data and large data transmission amount in the prior art.
In view of the above, one or more embodiments of the present specification provide an image communication system based on a specific model, including an image processing component and an image segmentation module, and an image receiving component for receiving an image.
The image processing component acquires an image through the camera, stores and identifies the image, marks the image after the identification, and analyzes pixel data of the marked image;
The image segmentation module is used for segmenting the marked image, acquiring corresponding colors of the segmented target image, separating the color image to obtain a gray image and color data of corresponding pixel points, and transmitting the gray image and the color data of the corresponding pixel points to the image receiving assembly through the data transmission module;
The image is segmented through the image segmentation module, so that the color data and gray image data of the image are completely acquired, and color errors and pixel loss in the conventional image transmission process are reduced.
The image receiving component receives color data and gray scale images respectively.
The image processing assembly includes: the device comprises an image acquisition module, a data processing module, an image recognition module and a data storage module, wherein the data processing module is electrically connected with the image acquisition module, the data processing module is electrically connected with the image recognition module, and the image recognition module is electrically connected with the data storage module;
the image is fed back to the data processing module through identification, and is stored through the data storage module.
Preferably, the image processing assembly further comprises: the system comprises a target image marking module and a marked image analysis module, wherein the data processing module is also in data connection with the target image marking module, and the target image marking module is in data connection with the marked image analysis module;
The mark image analysis module analyzes the target image processed by the target image marking module, and takes the stimulus quantity of the color RGB of the corresponding pixel point as an image mark.
Preferably, the image segmentation module includes: the image segmentation module and the target image storage module are used for transmitting the image data and the color RGB data output by the target image marking module to the image segmentation module and storing the target image data through the target image storage module;
The image segmentation module segments the image into corresponding color data and gray data to obtain two groups of data, namely a group of color RGB data and a group of basic gray image.
Preferably, the image segmentation module further includes: the color image acquisition module is in data connection with the color acquisition module, the color acquisition module is in data connection with the color image separation module, and the data transmission module is respectively and electrically connected with the color acquisition module and the color image separation module;
The color acquisition module acquires the transmitted group of color RGB data, and the color image separation module acquires the gray image and transmits the gray image through the data transmission module alone.
Preferably, the data transmission module at least comprises two radio frequency signal transmitting devices in frequency bands.
Preferably, the image receiving assembly includes: the device comprises an image receiving module, a color data receiving module and an image and data storage module, wherein the image receiving module and the color data receiving module are respectively connected with the data transmission module through radio frequency signals, and the image receiving module and the color data receiving module are respectively connected with the image and data storage module.
Preferably, the image receiving assembly further includes: the system comprises a central processing unit, a matrix data comparison module, an image pixel identification module and a layer matrix identification module, wherein the central processing unit is respectively connected with the matrix data comparison module, the image pixel identification module and the layer matrix identification module;
The matrix data comparison module performs matrix segmentation on the image and compares corresponding color RGB data, the layer matrix recognition module performs layer matrix recognition on the image to prevent errors generated by layer stacking, and the image pixel recognition module recognizes the image pixel data and judges the number of image pixels in the independent matrix.
From the above, it can be seen that, according to one or more embodiments of the present disclosure, two sets of data, that is, RGB data and gray image data, are respectively transmitted, and after being received, image matrix segmentation and layer matrix recognition are performed, and after being compared and spliced, image pixels are recognized, so that accuracy of image data is effectively ensured, and a problem that pixels are lost during image transmission in a conventional image communication manner or a problem that data volume is large during transmission is avoided.
Drawings
For a clearer description of one or more embodiments of the present description or of the solutions of the prior art, the following description will make a brief introduction to the drawings used in the embodiments or description of the prior art, it being apparent that the drawings in the following description are only one or more embodiments of the present description, and that other drawings may be obtained from these drawings without inventive effort to a person of ordinary skill in the art.
FIG. 1 is a schematic diagram of a system connection of an image processing assembly according to the present invention;
FIG. 2 is a schematic diagram of a system connection of an image receiving component according to the present invention;
FIG. 3 is a schematic diagram of a planar matrix structure according to the present invention.
In the figure: 1. an image processing component; 11. a data processing module; 12. an image acquisition module; 13. an image recognition module; 14. a data storage module; 15. a marker image analysis module; 16. a target image marking module; 2. an image segmentation module; 21. an image segmentation module; 22. a color acquisition module; 23. a color image separation module; 24. a data transmission module; 25. a target image storage module; 3. an image receiving component; 31. a central processing unit; 32. a matrix data comparison module; 33. an image pixel identification module; 34. an image and data storage module; 35. a layer matrix identification module; 36. an image receiving module; 37. and a color data receiving module.
Detailed Description
For the purposes of promoting an understanding of the principles and advantages of the disclosure, reference will now be made in detail to the following specific examples.
It is noted that unless otherwise defined, technical or scientific terms used in one or more embodiments of the present disclosure should be taken in a general sense as understood by one of ordinary skill in the art to which the present disclosure pertains. The use of the terms "first," "second," and the like in one or more embodiments of the present description does not denote any order, quantity, or importance, but rather the terms "first," "second," and the like are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", etc. are used merely to indicate relative positional relationships, which may also be changed when the absolute position of the object to be described is changed.
In the image receiving process, the image is divided into areas and an image matrix is established, the individual image areas in the image matrix are in a circular structure, meanwhile, the image receiving assembly 3 receives the images, the image receiving assembly takes the largest complete rectangular plane in the circular shape, and the fan-shaped structure at the edge is used as a splicing contrast group to carry out secondary identification on pixels.
Embodiment one:
as shown in fig. 1-3, an image communication system based on a specific model is provided, comprising an image processing component 1 and an image segmentation module 2, and an image receiving component 3 for receiving an image.
The image processing assembly 1 acquires an image through a camera, stores and identifies the image, marks the identified image, and analyzes pixel data of the marked image;
The image processing component 1 acquires the video shot by the camera, identifies whether a target image exists in each frame of data, and marks the pixel data of the target image of the image after analysis.
And respectively marking pixel data as a manual data acquisition mode of a data storage end through acquisition of an original image.
The image segmentation module 2 segments the marked image, acquires corresponding colors from the segmented target image, separates the color images to obtain gray images and color data of corresponding pixels, and transmits the gray images and the color data to the image receiving assembly 3 through the data transmission module 24;
the image is segmented through the image segmentation module 2, so that the color data and the gray image data of the image are completely acquired, and the occurrence of color errors and pixel loss in the conventional image transmission process is reduced.
The image receiving unit 3 receives color data and gray-scale images, respectively.
The image receiving component 3 receives images in two ways, and the data of the gray image can be used as a contrast group for color data transmission and also used as a follow-up adjustment plane substrate of RGB of the color data.
Embodiment two:
as shown in fig. 1-3, an image communication system based on a specific model is provided, comprising an image processing component 1 and an image segmentation module 2, and an image receiving component 3 for receiving an image.
The image processing assembly 1 acquires an image through a camera, stores and identifies the image, marks the identified image, and analyzes pixel data of the marked image;
And respectively marking pixel data as a manual data acquisition mode of a data storage end through acquisition of an original image.
The image segmentation module 2 segments the marked image, acquires corresponding colors from the segmented target image, separates the color images to obtain gray images and color data of corresponding pixels, and transmits the gray images and the color data to the image receiving assembly 3 through the data transmission module 24;
the image is segmented through the image segmentation module 2, so that the color data and the gray image data of the image are completely acquired, and the occurrence of color errors and pixel loss in the conventional image transmission process is reduced.
The image receiving unit 3 receives color data and gray-scale images, respectively.
The image receiving component 3 receives images in two ways, and the data of the gray image can be used as a contrast group for color data transmission and also used as a follow-up adjustment plane substrate of RGB of the color data.
The image processing assembly 1 comprises: the image acquisition device comprises an image acquisition module 12, a data processing module 11, an image recognition module 13 and a data storage module 14, wherein the data processing module 11 is electrically connected with the image acquisition module 12, the data processing module 11 is electrically connected with the image recognition module 13, and the image recognition module 13 is electrically connected with the data storage module 14;
Wherein the image is fed back to the data processing module 11 through recognition and is stored through the data storage module 14.
The image processing assembly 1 further comprises: the data processing module 11 also establishes data connection with the target image marking module 16, and the target image marking module 16 establishes data connection with the marked image analysis module 15;
the marker image analysis module 15 analyzes the target image processed by the target image marking module 16, and uses the stimulus amount of the color RGB corresponding to the pixel point as the image marker.
Through image acquisition and image analysis, the basic data of the image are effectively acquired, and the color RGB stimulation quantity of the corresponding pixel point is analyzed and determined.
Embodiment III:
as shown in fig. 1-3, an image communication system based on a specific model is provided, comprising an image processing component 1 and an image segmentation module 2, and an image receiving component 3 for receiving an image.
The image processing assembly 1 acquires an image through a camera, stores and identifies the image, marks the identified image, and analyzes pixel data of the marked image;
And respectively marking pixel data as a manual data acquisition mode of a data storage end through acquisition of an original image.
The image segmentation module 2 segments the marked image, acquires corresponding colors from the segmented target image, separates the color images to obtain gray images and color data of corresponding pixels, and transmits the gray images and the color data to the image receiving assembly 3 through the data transmission module 24;
the image is segmented through the image segmentation module 2, so that the color data and the gray image data of the image are completely acquired, and the occurrence of color errors and pixel loss in the conventional image transmission process is reduced.
The image receiving unit 3 receives color data and gray-scale images, respectively.
The image receiving component 3 receives images in two ways, and the data of the gray image can be used as a contrast group for color data transmission and also used as a follow-up adjustment plane substrate of RGB of the color data.
The image processing assembly 1 comprises: the image acquisition device comprises an image acquisition module 12, a data processing module 11, an image recognition module 13 and a data storage module 14, wherein the data processing module 11 is electrically connected with the image acquisition module 12, the data processing module 11 is electrically connected with the image recognition module 13, and the image recognition module 13 is electrically connected with the data storage module 14;
Wherein the image is fed back to the data processing module 11 through recognition and is stored through the data storage module 14.
The image processing assembly 1 further comprises: the data processing module 11 also establishes data connection with the target image marking module 16, and the target image marking module 16 establishes data connection with the marked image analysis module 15;
the marker image analysis module 15 analyzes the target image processed by the target image marking module 16, and uses the stimulus amount of the color RGB corresponding to the pixel point as the image marker.
Through image acquisition and image analysis, the basic data of the image are effectively acquired, and the color RGB stimulation quantity of the corresponding pixel point is analyzed and determined.
The image segmentation module 2 includes: the image segmentation module 21 and the target image storage module 25, the image data and the color RGB data output by the target image marking module 16 are transmitted to the image segmentation module 21, and the target image data is stored by the target image storage module 25;
the image segmentation module 21 segments the image into corresponding color data and gray data to obtain two sets of data, i.e., a set of color RGB data and a set of basic gray image.
The color RGB data of the image are obtained and converted independently, so that the basic requirement on transmission data is greatly reduced, and meanwhile, after the image obtained by the RGB data is divided into colors to form gray data, the color requirement of the image is reduced, the data transmission quantity is reduced, the data quantity is reduced during subsequent transmission, and the overall data quantity and the error probability of data transmission are reduced.
The image segmentation module 2 further includes: the color image acquisition module 22, the color image separation module 23 and the data transmission module 24, wherein the image segmentation module 21 is in data connection with the color acquisition module 22, the color acquisition module 22 is in data connection with the color image separation module 23, and the data transmission module 24 is respectively and electrically connected with the color acquisition module 22 and the color image separation module 23;
the color acquisition module 22 acquires the transmitted set of color RGB data, and the color image separation module 23 acquires the gray-scale image and transmits the gray-scale image through the data transmission module 24 alone.
The data transmission module 24 includes at least two radio frequency signal transmitting devices.
The radio frequency of the color RGB data radio frequency signal is higher than that of the gray image data transmission radio frequency signal.
Embodiment four:
As shown in fig. 2, the image receiving unit 3 includes: the image receiving module 36, the color data receiving module 37 and the image and data storage module 34, wherein the image receiving module 36 and the color data receiving module 37 respectively establish data connection with the data transmission module 24 through radio frequency signals, and the image receiving module 36 and the color data receiving module 37 respectively establish data connection with the image and data storage module 34.
The image receiving assembly 3 further comprises: the image display device comprises a central processing unit 31, a matrix data comparison module 32, an image pixel identification module 33 and a layer matrix identification module 35, wherein the central processing unit 31 is respectively connected with the matrix data comparison module 32, the image pixel identification module 33 and the layer matrix identification module 35;
the matrix data comparing module 32 performs matrix segmentation on the image, and compares corresponding color RGB data, the layer matrix identifying module 35 performs layer matrix identification on the image, so as to prevent errors generated by layer stacking, and the image pixel identifying module 33 identifies the image pixel data and determines the number of image pixels in the individual matrix.
And the areas of the image are established through image layer matrix identification, the acquired images are compared one by one, the accuracy of the images is ensured, and finally, whether the number of pixels of the images is correct or not is judged through pixel identification, and the RGB stimulation quantity of the images is supplemented, so that an effective target image is formed.
To sum up: the data processing module 11 receives the data of the image acquisition module 12, establishes bidirectional data circulation with the image recognition module 13, and the data storage module 14 receives and stores the data processed by the image recognition module 13; the data processing module 12 transmits the image processed by the image recognition module 13 to the target image marking module 16, and the target image marking module 16 transmits data to the marked image analysis module 15 and the image segmentation module 21 respectively; the marking image analysis module 15 transmits data back to the target image marking module 16, the target image marking module 16 transmits the data to the image segmentation module 21, the image segmented by the image segmentation module 21 is transmitted to the target image storage module 25 and the color acquisition module 22 in a unidirectional manner, the color acquisition module 22 acquires corresponding data and then transmits the corresponding data to the color image separation module 23, and the color acquisition module 22 and the color image separation module 23 respectively transmit the data to the image receiving assembly 3 through the data transmission module 24; the image receiving module 36 in the image receiving assembly 3 receives the image data separated by the color image separating module 23, the color data receiving module 37 receives the data of the color obtaining module 22 and respectively transmits the data to the image and data storage module 34, the central processing unit 31 respectively restores the color of the image area, the color restoration is compared and restored by the matrix data comparing module 32, the image pixel identifying module 33 and the image matrix identifying module 35, and the matrix data comparing module 32, the image pixel identifying module 33 and the image matrix identifying module 35 respectively establish two-way connection with the central processing unit 31.
The procedure is as follows.
Image color recognition program:
import cv2
import numpy as np
from sklearn.cluster import KMeans
def color_recognition(image_path, num_colors=5):
# read image
image = cv2.imread(image_path)
# Convert image to RGB format
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# Convert image into one-dimensional array
pixels = image.reshape(-1, 3)
Clustering pixel colors using K-means algorithm
kmeans = KMeans(n_clusters=num_colors)
kmeans.fit(pixels)
# Obtain color value of clustering center
colors = kmeans.cluster_centers_.astype(int)
return colors
def main():
# Image path
image_path = "your_image.jpg"
# Call color recognition function
colors = color_recognition(image_path)
Print the identified color value #
Print (' recognized color: ")
for color in colors:
print("RGB:", color)
if __name__ == "__main__":
main()
Image gray scale adjustment program:
import cv2
def adjust_grayscale(image_path, brightness_factor=1.0):
# read image
image = cv2.imread(image_path)
# Convert image to grayscale image
grayscale_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Optional: adjusting brightness of gray scale image
adjusted_image = cv2.convertScaleAbs(grayscale_image, alpha=brightness_factor, beta=0)
return adjusted_image
def main():
# Image path
image_path = "your_image.jpg"
# Brightness adjustment factor (optionally, 1.0 means not adjusted)
brightness_factor = 1.0
# Call gray-scale adjustment function
adjusted_image = adjust_grayscale(image_path, brightness_factor)
# Display original image and adjusted image
cv2.imshow("Original Image", cv2.imread(image_path))
cv2.imshow("Adjusted Grayscale Image", adjusted_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
Image pixel recognition program:
import cv2
def get_pixel_value(image_path, x, y):
# read image
image = cv2.imread(image_path)
# Acquisition of image size
height, width, _ = image.shape
# Ensure that a given coordinate is within the image
if x >= 0 and x < width and y >= 0 and y < height:
# Obtain pixel value of specified position
pixel_value = image[y, x]
return pixel_value
else:
Print ('specified coordinates out of image range')
return None
def main():
# Image path
image_path = "your_image.jpg"
Coordinates of the pixels to be identified #
x = 100
y = 150
# Acquisition of pixel values
pixel_value = get_pixel_value(image_path, x, y)
if pixel_value is not None:
The pixel value at print ("coordinates ({ }, { }) is: { }". Format (x, y, pixel_value))
if __name__ == "__main__":
main()
It should be noted that the methods of one or more embodiments of the present description may be performed by a single device, such as a computer or server. The method of the embodiment can also be applied to a distributed scene, and is completed by mutually matching a plurality of devices.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
For convenience of description, the above devices are described as being functionally divided into various modules, respectively. Of course, the functions of each module may be implemented in one or more pieces of software and/or hardware when implementing one or more embodiments of the present description.
The device of the foregoing embodiment is configured to implement the corresponding method in the foregoing embodiment, and has the beneficial effects of the corresponding method embodiment, which is not described herein.
Those of ordinary skill in the art will appreciate that: the discussion of any of the embodiments above is merely exemplary and is not intended to suggest that the scope of the disclosure, including the claims, is limited to this example.
While the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of those embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.
The present disclosure is intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Any omissions, modifications, equivalents, improvements, and the like, which are within the spirit and principles of the one or more embodiments of the disclosure, are therefore intended to be included within the scope of the disclosure.
Claims (1)
1. An image communication system based on a specific model, comprising an image processing component (1) and an image segmentation module (2), and an image receiving component (3) for receiving an image, characterized in that:
The image processing assembly (1) acquires an image through a camera, stores and identifies the image, marks the identified image, and analyzes pixel data of the marked image;
The image segmentation module (2) segments the marked image, acquires corresponding colors from the segmented target image, separates the color images to obtain gray images and color data of corresponding pixel points, and transmits the gray images and the color data to the image receiving assembly (3) through the data transmission module (24);
the image receiving component (3) is used for respectively receiving color data and gray images;
The image processing assembly (1) comprises: the device comprises an image acquisition module (12), a data processing module (11), an image recognition module (13) and a data storage module (14), wherein the data processing module (11) is electrically connected with the image acquisition module (12), the data processing module (11) is electrically connected with the image recognition module (13), and the image recognition module (13) is electrically connected with the data storage module (14);
the image is fed back to the data processing module (11) through identification, and is stored through the data storage module (14);
the image processing assembly (1) further comprises: the system comprises a target image marking module (16) and a marked image analysis module (15), wherein the data processing module (11) is also in data connection with the target image marking module (16), and the target image marking module (16) is in data connection with the marked image analysis module (15);
the marking image analysis module (15) analyzes the target image processed by the target image marking module (16) and takes the stimulus quantity of the color RGB of the corresponding pixel point as an image marking;
the image segmentation module (2) comprises: the image segmentation module (21) and the target image storage module (25), wherein the image data and the color RGB data output by the target image marking module (16) are transmitted to the image segmentation module (21), and the target image data is stored through the target image storage module (25);
the image segmentation module (21) segments corresponding color data and gray data of the image to obtain two groups of data which are a group of color RGB data and a group of basic gray image respectively;
The image segmentation module (2) further comprises: the color image acquisition device comprises a color acquisition module (22), a color image separation module (23) and a data transmission module (24), wherein the image segmentation module (21) is in data connection with the color acquisition module (22), the color acquisition module (22) is in data connection with the color image separation module (23), and the data transmission module (24) is respectively and electrically connected with the color acquisition module (22) and the color image separation module (23);
The color acquisition module (22) acquires the transmitted group of color RGB data, and the color image separation module (23) acquires the gray level image and transmits the gray level image through the data transmission module (24) alone;
the data transmission module (24) at least comprises radio frequency signal transmitting devices of two frequency bands;
the image receiving assembly (3) comprises: the device comprises an image receiving module (36), a color data receiving module (37) and an image and data storage module (34), wherein the image receiving module (36) and the color data receiving module (37) are respectively connected with a data transmission module (24) through radio frequency signals, and the image receiving module (36) and the color data receiving module (37) are respectively connected with the image and data storage module (34) in a data mode;
The image receiving assembly (3) further comprises: the system comprises a central processing unit (31), a matrix data comparison module (32), an image pixel identification module (33) and a layer matrix identification module (35), wherein the central processing unit (31) is respectively connected with the matrix data comparison module (32), the image pixel identification module (33) and the layer matrix identification module (35) in a data manner;
The matrix data comparison module (32) performs matrix segmentation on the image, and compares corresponding color RGB data, the layer matrix recognition module (35) performs layer matrix recognition on the image, prevents errors generated by layer stacking, and the image pixel recognition module (33) recognizes the image pixel data and judges the number of image pixels in the independent matrix.
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