Extraction and Recognition of Speed Limit Signs in Night-scene Videos

Kageyama, Yoichi; Suzuki, Kazuto; Ishizawa, Chikako; Suzuki, Takuya

doi:10.12792/jiiae.6.29

Cited by 3 publications

(7 citation statements)

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“…To compare with the conventional study [15], recognition experiments using two datasets were also conducted. The 80 km/h , and 50 km/h.…”

Section: Experiments Results For Speed Limit Signsmentioning

confidence: 99%

“…In this section, we present the four advantages of the proposed recognition method over the conventional method [15]. In the conventional method, the discriminant analysis used focuses on the entire area of the extraction image during the binarization process (our previous method [15] p. 2, line 38). However, the proposed method focuses only on the central area of the extraction image.…”

Section: Recognition Methods For Speed Limit Signsmentioning

confidence: 99%

“…In this section, we present the four advantages of the proposed recognition method over the conventional method [15].…”

Section: Advantages and Effectiveness Of The Proposed Recognition Metmentioning

confidence: 99%

“…In our previous studies, we developed certain processes for the extraction and recognition of speed limit signs at night [14]. The accuracy and processing time [15] of these processes were improved. It was evident from these studies that employing the template-matching process is effective for this.…”

Section: Introductionmentioning

confidence: 99%

“…It was possible to divide the common number and the feature numbers, even when the extraction image was inclined.Figure 7shows that one number is included in another area when divided at the center of the extraction image and the advantage point of the proposed method. On the other hand, the area is divided in half for the extraction image of the speed limit sign in our previous method (our previous method[15] p. 2, lines 44 and 45). • The conventional method performs recognition by template matching using the complete image of the speed sign (our previous method [15] p. 2,…”

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confidence: 99%

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Recognition Method for Speed Limit Signs and its Applicability in Recognition of Vehicle Entry Prohibition Signs at Night

Suzuki

Kageyama

Ishizawa

2020

IEEJ Transactions Elec Engng

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Recently, cameras with sensing technology have been used in vehicles to prevent traffic accidents. Although vehicle drivers can visually notice road signs, a recent study developed a recognition system for road signs to prevent traffic accidents. However, this system does not always perform the intended operation and encounters issues if the vehicle is driven at night, the road environment is bad, or the sign is discolored due to aging. Furthermore, the death rate due to speed violations at night is higher compared with that due to other traffic violations. The drivers and existing systems may have difficulties recognizing these signs as they are susceptible to other lights on the roads, such as traffic lights, streetlights, and vehicle headlights at night. Therefore, we propose a recognition method for speed limit signs that are difficult for drivers to recognize at night. In addition, the proposed method is applied to recognize vehicle entry prohibition signs at night. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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“…To compare with the conventional study [15], recognition experiments using two datasets were also conducted. The 80 km/h , and 50 km/h.…”

Section: Experiments Results For Speed Limit Signsmentioning

confidence: 99%

Section: Recognition Methods For Speed Limit Signsmentioning

confidence: 99%

“…In this section, we present the four advantages of the proposed recognition method over the conventional method [15].…”

Section: Advantages and Effectiveness Of The Proposed Recognition Metmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Recognition Method for Speed Limit Signs and its Applicability in Recognition of Vehicle Entry Prohibition Signs at Night

Suzuki

Kageyama

Ishizawa

2020

IEEJ Transactions Elec Engng

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A Study on Extraction and Recognition of Speed Limit Signs to Assist Drivers of Vehicles

Suzuki

Kageyama

Ishizawa

2018

Proceedings of the 6th IIAE International Conference on Intelligent Systems and Image Processing 2018

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Road signs provide important information that guides and regulates the behavior of drivers and pedestrians to make their travel safer and more comfortable. However, safety might be compromised by disregarding the speed limit signs. The rate of accidental death due to speed limit violations is extremely high at night. We can address this issue by implementing road sign recognition using videos. This can contribute to the reduction of traffic accidents.In this study, we propose a novel extraction method that focuses on the outlines of signs and a recognition method that focuses on number symbols in signs in videos at night.

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Traffic Road Sign Recognition Using Multi-CNN Model for Autonomous Ground Vehicles

2024

European Economic Letters

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Detecting and recognizing the traffic road sign plays a significant role in autonomous vehicles while processing the details regarding each road signs. This research proposed a novel Multi Convolutional Neural Network (M-CNN) for recognizing different traffic signs. In this model, four different CNN structures are applied for processing various road signs. So, the high-level and low-level features are extracted to classify the signs into a proper class in driver-assisted autonomous vehicles. Here, the developed model has produced outstanding results while classifying different real-time traffic signs. The efficiency of the proposed model has been assessed by a well-known database named German Traffic Sign Recognition Benchmark (GTSRB). Moreover, the simulation outcomes demonstrate that the M-CNN model has certain advantages while detecting various traffic signs. Simulation results indicate that the proposed M-CNN model has a higher recognition rate and reduced processing time when compared to Machine Learning (ML) and Deep Learning (DL) models.

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Extraction and Recognition of Speed Limit Signs in Night-scene Videos

Cited by 3 publications

References 0 publications

Recognition Method for Speed Limit Signs and its Applicability in Recognition of Vehicle Entry Prohibition Signs at Night

Recognition Method for Speed Limit Signs and its Applicability in Recognition of Vehicle Entry Prohibition Signs at Night

A Study on Extraction and Recognition of Speed Limit Signs to Assist Drivers of Vehicles

Traffic Road Sign Recognition Using Multi-CNN Model for Autonomous Ground Vehicles

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