How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

Image recognition is an important field of artificial intelligence. With the rapid development of image processing and analysis technology, image recognition has been widely used in medical, retail, transportation and other fields. Image recognition technology also plays an irreplaceable role in the automated test system for car audio-visual entertainment. Today, the editor will break down in detail how to use LabVIEW to realize image recognition of car instrumentation.

Image recognition is an important field of artificial intelligence. With the rapid development of image processing and analysis technology, image recognition has been widely used in medical, retail, transportation and other fields. Image recognition technology also plays an irreplaceable role in the automated test system for car audio-visual entertainment. Today, the editor will break down in detail how to use LabVIEW to realize image recognition of car instrumentation.

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(LabVIEW Image Recognition System)

Step1 Image acquisition

Image acquisition is the premise of image recognition, taking the GigE industrial camera as an example. Image acquisition requires a series of functions in the NI-IMAQdx driver module. The process is as follows:

1. Use the IMAQdx Open Camera.vi function to connect and open the selected camera;

2. Obtain the image through the IMAQdx Grab.vi function;

3. Use the IMAQdx Write File.vi function to save the image to a folder in the selected format, including BMP, PNG, JPEG, TIFF, etc.

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(image acquisition program)

Step2 Image processing

Image processing is the process of denoising, enhancing, restoring, segmenting, and extracting features through a computer. Here is a brief introduction to several basic methods of image processing using the functions of the Vision Development Module software package in LabVIEW – image grayscale, image binarization, and image enhancement.

1. Image grayscale

The images collected by industrial cameras are generally in RGB color mode. However, RGB mode cannot reflect the morphological characteristics of the image, and can only be adjusted from the principle of optics. Therefore, when processing images, the three components of RGB should be processed separately. Using the IMAQ Extract Single Color Plane.vi function in LabVIEW software can realize the grayscale processing of the image. The image grayscale processing program and processing results are shown in the following figure:

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(grayscale handler)

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(grayscale processing result)

2. Image binarization

Image binarization processing is to make the whole image show obvious black and white effect by setting the gray value of each pixel on the image to 0 or 255. In LabVIEW, use the IMAQ Threshold.vi function to select an appropriate threshold for the grayscale image, so as to obtain a binarized image that can reflect the overall and local characteristics of the image. The handler and processing result are shown in the following figure:

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(binarization handler)

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(Binarization result)

3. Image enhancement

Image enhancement refers to highlighting necessary information in an image according to user needs, while attenuating or removing unwanted information. Image enhancement is the most basic means of image processing. Using the IMAQ BCGLookup.vi function in LabVIEW software to correct the grayscale image can improve the visual effect of the image, thereby providing an intuitive, clear image suitable for analysis. The image enhancement processing program and processing results are shown in the following figure:

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(image enhancement handler)

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(image enhancement processing result)

Step3 Image recognition

The collected images are processed, and the next step is to identify them. The computer is used to process, analyze and understand the objects in the image, and simulate the process of human cognition and understanding, so as to recognize the targets and objects of various modes.

The image recognition of automobile instruments mainly includes alarm icon recognition and OCR recognition. The principles of the two recognition modes are basically the same. First, the original image is preprocessed, and then the features are extracted and stored in the training library. The information in the library is compared, and the identification result is finally obtained. The two identification schemes are shown in the following figure:

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(icon recognition)

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

(OCR recognition)

1. Icon training/recognition

In the Edit Icon Classifier interface, the icon recognition function of the screen can be configured, and the shape, color and position of the sample icon can be stored in the training library. The configuration interface is shown in the figure below. The left side of the interface is the latest image collected by the device, the right side is the information list of recognizable icons, and the lower right corner is the image Display of the icon.

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

At the same time, you can view and delete color learning resources on the Edit Color Classifier interface. The left side of the interface displays the current learning resources identified by color, and in the Browser Display on the right, you can choose to display all learning resources or display the corresponding learning resources by color category.

How to Use LabVIEW to Realize Image Recognition of Car Instrumentation

2. OCR training/recognition

Before reading the text or characters of the image, the character samples are trained by the NI OCR Training module, and the library file in abc format is generated. Then, in the initialization part of the code, use the IMAQ OCR Read Character Set File.vi function to read the NI OCR Training interface and create a session, and realize the function of character recognition by calling the abc file in the program.

So far, the complete process from image acquisition to image processing to image recognition has been completed. At present, this image recognition system has been used by well-known domestic automobile companies to identify the display of automobile instrument alarm icons, the flashing frequency of dynamic icons, and the text of fault alarms.

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