A Unified Framework for Automobile Instrument Detection System

Zhang, Jiawei; Liu, Yu; Yuan, Li; Yu, Jinyong

doi:10.1109/tim.2022.3147881

Cited by 4 publications

(5 citation statements)

References 24 publications

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“…Pointer detection is essential for meter reading recognition [42] pointer recognition methods mainly include silhouette methods, which compare the image to be detected with a template image to obtain the position of the meter pointer with respect to the initial pointer. Hough linear detection method, where the meter image is segmented by threshold segmentation and edge detection, and then the pointer straight line equation is fitted by Hough straight line fitting.…”

Section: Results Of the Pointer Fitting Experimentsmentioning

confidence: 99%

“…An accurate fit to the linear equation for the meter pointer can provide more favorable information for meter reading recognition [42]. Existing methods for pointer recognition start by detecting pointer regions from the dashboard.…”

Section: The Pointer Linear Equations Were Fitted Using the Methods O...mentioning

confidence: 99%

“…A similar process was used by Wang et al [41]. Zhang et al [42] proposed the EF-SSD algorithm to detect pointers in automobile instrument clusters, which improves the accuracy of pointer localization by calculating the distance between fuzzy sets and measuring how much each pixel belongs to the edge of the pointer. Ma et al [43] effectively solved the pointer shading problem using a symmetry-based binarized threshold segmentation method.…”

Section: Related Workmentioning

confidence: 99%

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Application of Swin-Unet for pointer detection and automatic calculation of readings in pointer-type meters

Zhang,

Ji,

Yang

et al. 2023

Meas. Sci. Technol.

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Pointer-type meters are widely used in military, industrial, and aerospace applications. In this paper, we propose a method to automatically calculate the readings of pointer-type meters that exhibits strong robustness to various situations, such as complex backgrounds, tilted meters, blurred images, and meter images with uneven illumination. First, the mask maps of scale and pointers are obtained using the Swin-Unet semantic segmentation network. For the mask map of scale, the Swin Transformer image classification network is used to identify the values of the scale and the coordinates of the centroids of the scale, and for the mask map of the pointer, the least skeleton circle method is proposed to fit the linear equation of the pointer. Second, the influence of the pointer and several adjacent scale on the meter reading is considered, and the weighted angle method (WAM) is proposed to calculate the meter reading. In order to verify the robustness of the algorithm in this paper, the pointer detection method is compared with the traditional pointer detection method, and it is found that the pointer detection method in this paper works better, and the pointer detection algorithm in this paper is applied to different semantic segmentation results, and it is verified that the pointer detection algorithm in this paper can be well adapted to different semantic segmentation results. This paper also compares the proposed algorithm with the existing meter reading calculation methods. The experiments show that using WAM on uncorrected meter images reduces the error by 30% compared with the traditional angle method, and using WAM on corrected meter images reduces the error by about 50%, which finally verifies the effectiveness of the algorithm in this paper.

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Section: Results Of the Pointer Fitting Experimentsmentioning

confidence: 99%

Section: The Pointer Linear Equations Were Fitted Using the Methods O...mentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Application of Swin-Unet for pointer detection and automatic calculation of readings in pointer-type meters

Zhang,

Ji,

Yang

et al. 2023

Meas. Sci. Technol.

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show abstract

“…Consequently, an effective reading recognition method will get high accuracy recognition results. For the identification of the pointer reading, the most important thing is to detect the position of the pointer [27]. For the detection of the pointer, there are common methods such as the region growth method, depth learning based detection method and Hough straight line detection method.…”

Section: Pointer Reading Identificationmentioning

confidence: 99%

Correction and pointer reading recognition of circular pointer meter

Zhang

Zhao

et al. 2022

Meas. Sci. Technol.

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For the meter images collected in the actual environment, there is the possibility of tilt and rotation. This paper presents a method to calibrate the circular pointer-type meter based on YOLOv5s network. The convolution neural network (CNN) framework is used to detect the scale value in the meter panel as the key point, the position information and value information of the detected scale value are used to fit the elliptic equation of the position of the scale value with the least square method for perspective correction and rotation correction of the meter, and the corrected meter image is used to obtain the meter pointer reading. This paper proposes the weighted angle method to read the meter reading. The accumulated error of the meter image after multiple transformations is eliminated. Finally, comparing the pointer detection method of this paper with the traditional pointer detection method, the error of this detection method is smaller; comparing the meter reading results before and after correction, the meter reading error after correction is 50\% less than before correction, and comparing the method of this paper with other mainstream methods, it proves the effectiveness of the correction method of this paper.

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“…Highly specialized products such as self-driving vehicles, electric propulsion-based vehicles, racing vehicles, and intelligent vehicles require many signals to be acquired and analyzed to achieve optimal performances. In this point of view, several sensors can be implemented in motorcycles and cars for the optimization of control strategy, as well as for condition monitoring and diagnostics [7], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Inertial Measurement Units Performances Under Dynamic Conditions

Patrizi

Carratù

Ciani

et al. 2023

IEEE Trans. Instrum. Meas.

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Inertial measurement units (IMUs) are nowadays widespread in the automotive industry. Micro-electromechanical systems (MEMS) IMUs are expanding because of several advantages of this technology. However, a significant research gap neglected by both manufacturers and recent literature regards the behavior of their performances under dynamic conditions and operating under harsh environments. Before the actual installation on the field, the performances of such devices in the presence of vibration sources and mechanical load stresses must be investigated. Trying to fill this gap, this article investigates the behavior of MEMS-based IMU under dynamic conditions and random vibration tests. The proposed experimental platform also includes a specific device used to generate repeatable, controlled movement, ensuring a dynamic characterization. The analysis consists of both time and frequency domains, with specific metrics defined to evaluate the negative effects of harsh conditions on IMU performances. The results aim to highlight the limitation of the device under test when used in the automotive industry, i.e., in the presence of significant vibration noise.

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A Unified Framework for Automobile Instrument Detection System

Cited by 4 publications

References 24 publications

Application of Swin-Unet for pointer detection and automatic calculation of readings in pointer-type meters

Application of Swin-Unet for pointer detection and automatic calculation of readings in pointer-type meters

Correction and pointer reading recognition of circular pointer meter

Analysis of Inertial Measurement Units Performances Under Dynamic Conditions

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