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A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle

A specific target and smart car technology, applied in image data processing, instruments, calculations, etc., can solve the problems of complex topological feature extraction, complex extraction methods, and large amount of calculation, so as to reduce the interference of light and background noise and avoid extraction Effects of inaccuracy, good real-time and robustness

Active Publication Date: 2018-12-11
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

The extraction methods of these three kinds of invariant features are relatively complicated, and the amount of calculation is relatively large, especially the extraction of topological features is the most complicated, and it is difficult to be applied in the field of image processing with high real-time requirements.

Method used

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  • A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle
  • A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle
  • A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle

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Embodiment Construction

[0038] Step 1) Given the target operating domain O and divide it evenly into A regions of the same size, dispatch A smart cars to start searching from the A regions, and the target existence probability of each region is P i,g,k , i=1,2...A, the k represents the current moment, i represents the number of the car, g=g(m,n) represents one of the areas (the (m,n) represents the center coordinates of the area );

[0039] Step 2) Input the target image to be recognized, and perform gray-level thresholding processing on the image to obtain its two-dimensional digitized gray-scale image f(M,N), whose MN pixels are MN particles on the XOY plane, record The centroid coordinates (cx, cy) of the image, the gray value of each pixel point (x, y) is f(x, y) to represent the quality of the corresponding mass point; the target is measured by the normalized rotation vector (NMI) method Identification and tracking, the specific steps are as follows:

[0040] Step 2.1) Calculate the moment of ...

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Abstract

The invention discloses a method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicles. The method includes: firstly, a target operation fieldO is initialized and divided into A small blocks, and A intelligent vehicles are used for searching in the A regions. then, by calculating the normalized rotation vector (NMI) of one of the targets in the target group, and the intelligent vehicle continuously collects and preprocesses the images in the search process; the NMI value of the captured image is matched with the input value in advance,if the NMI value is equal, the measurement result is true, otherwise, the target is not found; The measured values are then used as inputs to a single smart car i and the maps are updated separatelyaccording to the Bayesian rules. The nonlinear transformation of a probability graph is introduced to simplify the computation by linearized Bayesian updating. Finally, a distributed fusion scheme similar to consensus is provided, which is applied to map fusion of multi-vehicle, and a new dispersion probability graph is obtained.

Description

technical field [0001] The invention relates to a method for realizing collaborative search, identification and tracking of a specific target group by multiple smart cars, which mainly utilizes a distributed search algorithm, wireless sensor communication technology and a method of extracting normalized rotation vector features to quickly identify and track a large area. Tracking a specific target group belongs to the field of wireless sensor networks, mathematical methods and digital image processing. Background technique [0002] The problem of target search recognition and tracking has always been a very active part of the research field, and it has a very wide range of applications in the military field, intelligent transportation, security defense and other fields. In terms of cooperative control of multiple agents, the current typical research mainly includes cooperative reconnaissance, cooperative search, cooperative target tracking, cooperative positioning and format...

Claims

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Application Information

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IPC IPC(8): G06T7/292G06T5/00
CPCG06T7/292G06T2207/20221G06T5/70
Inventor 陈志狄小娟岳文静汪皓平龚凯
Owner NANJING UNIV OF POSTS & TELECOMM
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