CN-116091825-B - Nixie tube content identification method and device, electronic equipment and storage medium

CN116091825BCN 116091825 BCN116091825 BCN 116091825BCN-116091825-B

Abstract

The invention relates to the technical field of digital identification, in particular to a nixie tube content identification method, a nixie tube content identification device, electronic equipment and a storage medium, wherein the method comprises the steps of obtaining a continuous video image sequence of a nixie tube, and obtaining position information of a character display section of the nixie tube according to a preset frame number by using a template matching algorithm; the device comprises a nixie tube and a PC end connected with the nixie tube through signals, wherein the nixie tube and the PC end are configured to be in an asynchronous state, and the PC end comprises an acquisition module, a position identification unit, a brightness identification unit and a training module. The method aims to solve the problem of false identification caused by uneven brightness and incomplete brightness in the process of identifying the nixie tube content.

Inventors

WANG HUI
HU BIN
RAN YONG
ZHANG GAOHONG
Li Cuibo
TANG YUANJIAN

Assignees

成都交大光芒科技股份有限公司

Dates

Publication Date: 20260512
Application Date: 20230106

Claims (5)

1. The nixie tube content identification method is characterized by comprising the following steps of: the method for acquiring the continuous video image sequence of the nixie tube comprises the steps of utilizing a corner matching method to carry out matching identification on the position information of a display segment, and specifically comprises the following steps of: Acquiring original image information of a nixie tube and target image information in a video image sequence, and extracting key feature points by using a feature point extraction algorithm, wherein the key feature points at least comprise corner points, edge points, bright points of a dark area and dark points of the bright area; positioning the key feature points, extracting feature vectors, and comparing to obtain mutually matched key feature points; eliminating noise by utilizing a RANSAC algorithm aiming at key feature points matched with each other so as to acquire specific position information of a display segment; Recognizing the bright and dark states of the character display section of the nixie tube by using a Support Vector Machine (SVM), wherein the SVM is used for performing multi-frame recognition on the video image sequence; acquiring brightness sequence units of a nixie tube character display section under a preset frame number according to a preset nixie tube arrangement mode, wherein the preset nixie tube arrangement mode specifically comprises the steps of taking the sequence of the display section refreshed by the nixie tube as an arrangement rule of the brightness sequence units; classifying the brightness sequence units by using a deep learning method and outputting a recognition result, wherein the method specifically comprises the following steps: Manually labeling the brightness sequence units and obtaining a labeling data set; training based on the labeling data set to obtain a classification model; And identifying the brightness sequence unit by using the classification model and outputting an identification result.
2. The method of claim 1, wherein the training based on the labeled dataset to obtain the classification model specifically comprises: and training the labeling data set by using Resnet-50 convolutional neural network models to obtain a classification model.
3. The nixie tube content identification device is characterized by being applied to the nixie tube content identification method of any one of claims 1 to 2, and comprising a nixie tube and a PC end connected with the nixie tube through signals, wherein the nixie tube and the PC end are configured to be in an unsynchronized state, and the PC end comprises: the acquisition module is configured to acquire a continuous video image sequence of the nixie tube; the position identification unit is configured to acquire position information of a character display section of the nixie tube according to a preset frame number by using a template matching algorithm; the brightness recognition unit is configured to obtain a brightness sequence unit of a nixie tube character display section under a preset frame number according to a preset nixie tube arrangement mode; and the training module is configured to classify the brightness sequence units by using a deep learning method and output the recognition result.
4. An electronic device comprising a processor and a memory communicatively coupled to the processor, wherein the memory stores instructions executable by the processor to enable the processor to perform the steps of the nixie tube content identification method of any one of claims 1-2.
5. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a program for realizing a nixie tube content recognition method, the program for realizing the nixie tube content recognition method being executed by a processor to realize the steps of the content recognition method according to any one of claims 1 to 2.

Description

Nixie tube content identification method and device, electronic equipment and storage medium Technical Field The invention relates to the technical field of digital identification, in particular to a nixie tube content identification method, a nixie tube content identification device, electronic equipment and a storage medium. Background The nixie tube is one of LED display screens, is widely applied to meters such as voltmeters, ammeter, thermometer and the like in a transformer substation due to low price and convenient use, and displays numerical information of related meters through the nixie tube; the existing nixie tube LED display screen is characterized in that a display unit of the LED display screen is displayed asynchronously due to the driving mode principle, for example, an auxiliary monitoring system of a transformer substation is required to carry out all-weather inspection on equipment meters of the transformer substation, so that the accurate perception of the states and parameters of the equipment meters is realized, the manual inspection intensity is reduced, and finally unmanned inspection is realized; The invention patent nixie tube dynamic display identification method and system with the publication number of CN108182400A is characterized in that the dynamic display period of the nixie tube is acquired, the dynamic scanning period of the nixie tube is set as the exposure time of a camera through a PC end, so that the complete acquisition of the nixie tube content is realized, and further, the identification is realized, but the mode has higher requirements on the camera and the system, the camera is required to be controllable, the LED display screen is required to be synchronously linked with the system, and the scheme can solve the problem of incomplete acquired images, but has a certain difficulty in system deployment. Therefore, we propose a nixie tube content identification method, a nixie tube content identification device, an electronic device and a storage medium. Disclosure of Invention The invention aims to provide a nixie tube content identification method, a nixie tube content identification device, electronic equipment and a storage medium, which are used for solving the problem of false identification caused by uneven brightness and incomplete brightness in the nixie tube content identification process. The technical scheme of the first aspect of the invention provides a nixie tube content identification method, which comprises the following steps: acquiring a continuous video image sequence of the nixie tube, and acquiring position information of a character display section of the nixie tube according to a preset frame number by using a template matching algorithm; Recognizing the bright and dark states of the character display section of the nixie tube by using a Support Vector Machine (SVM); Acquiring a brightness sequence unit of a nixie tube character display section under a preset frame number according to a preset nixie tube arrangement mode; and classifying the brightness sequence units by using a deep learning method and outputting the recognition result. Further, the template matching algorithm specifically comprises the steps of matching and identifying the position information of the display segment by utilizing a corner matching method, and specifically comprises the following steps: acquiring original image information of a nixie tube and target image information in a video image sequence, and extracting key feature points by using a feature point extraction algorithm; positioning the key feature points, extracting feature vectors, and comparing to obtain mutually matched key feature points; And eliminating noise by utilizing a RANSAC algorithm aiming at the key feature points matched with each other so as to acquire the specific position information of the display segment. Further, the key feature points include at least corner points, edge points, two points of a dark area, and a dark point of a bright area. Further, the preset nixie tube arrangement mode specifically comprises the step of taking the sequence of refreshing display segments of the nixie tube as an arrangement rule of brightness sequence units. Further, the method for performing the deep learning on the brightness sequence units and outputting the recognition result specifically includes: Manually labeling the brightness sequence units and obtaining a labeling data set; training based on the labeling data set to obtain a classification model; And identifying the brightness sequence unit by using the classification model and outputting an identification result. Further, the training based on the labeling data set to obtain the classification model specifically includes: and training the labeling data set by using Resnet-50 convolutional neural network models to obtain a classification model. The technical scheme of the second aspect of the invention provides a nixie tube content recognition