Real-time recognition of road traffic sign in moving scene image using new image filter

Hirose, Keikichi; Asakura, Toshiyuki; Aoyagi, Yuji

doi:10.1109/sice.2000.889645

Cited by 15 publications

(3 citation statements)

References 1 publication

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“…In Top-Down phase, we choose Simple Vector Filter proposed by T. Asakura etc [12] as a priori guide. The filter can highly extract specific colour and remove profile and have good segmentation results for red, blue and yellow.…”

Section: Btw O-way Integration Methods Of Target Detectionmentioning

confidence: 99%

Traffic Sign Detection Based on Biologically Visual Mechanism

Zhu

2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:TSR (Traffic sign recognition) is an important problem in ITS (intelligent traffic system), which is being paid more and more attention for realizing drivers assisting system and unmanned vehicle etc. TSR consists of two steps: detection and recognition, and this paper describe a new traffic sign detection method. The design principle of the traffic sign is comply with the visual attention mechanism of human, so we propose a method using visual attention mechanism to detect traffic sign ,which is reasonable. In our method, the whole scene will firstly be analyzed by visual attention model to acquire the area where traffic signs might be placed. And then, these candidate areas will be analyzed according to the shape characteristics of the traffic sign to detect traffic signs. In traffic sign detection experiments, the result shows the proposed method is effectively and robust than other existing saliency detection method.

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Section: Btw O-way Integration Methods Of Target Detectionmentioning

confidence: 99%

Traffic Sign Detection Based on Biologically Visual Mechanism

Zhu

2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Eigen‐Colour [12], a colour model, was proposed to detect traffic signs, which is different from the RGB model. In order to use more prior knowledge, the works of [13–16] assembled colour clues in traditional methods. According to the unique shape information of traffic signs, symmetry characteristics, length and direction of polygons [17] were utilised to locate traffic signs accurately.…”

Section: Related Workmentioning

confidence: 99%

Scale‐aware limited deformable convolutional neural networks for traffic sign detection and classification

Liu

Shen

Fan

et al. 2020

IET intell. transp. syst

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“…On the color segmentation: Asakura [1] proposed simple vector filter (SVF) which can extract specified color pixels with high speed. Huang Zhiyong and Sun Guangmin [2] used fixed thresholds of RGB substruction to extract red and blue pixels.…”

Section: Introductionmentioning

confidence: 99%

Detection for Deformed and Sheltered Circular Traffic Signs

Bao

2015

MATEC Web of Conferences

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Real-time recognition of road traffic sign in moving scene image using new image filter

Cited by 15 publications

References 1 publication

Traffic Sign Detection Based on Biologically Visual Mechanism

Traffic Sign Detection Based on Biologically Visual Mechanism

Scale‐aware limited deformable convolutional neural networks for traffic sign detection and classification

Detection for Deformed and Sheltered Circular Traffic Signs

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