Mixed Vertical-and-Horizontal-Text Traffic Sign Detection and Recognition for Street-Level Scene
Much effort has been dedicated to text-based traffic sign detection and recognition. However, there are still two problems. First, unlike English traffic signs with only horizontal text, Chinese traffic signs have both horizontal and vertical text. To the best of our knowledge, there is nothing in t...
Ausführliche Beschreibung
Autor*in: |
Jiefeng Guo [verfasserIn] Rongxuan You [verfasserIn] Lianfen Huang [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2020 |
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Übergeordnetes Werk: |
In: IEEE Access - IEEE, 2014, 8(2020), Seite 69413-69425 |
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Übergeordnetes Werk: |
volume:8 ; year:2020 ; pages:69413-69425 |
Links: |
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DOI / URN: |
10.1109/ACCESS.2020.2986500 |
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Katalog-ID: |
DOAJ016105257 |
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520 | |a Much effort has been dedicated to text-based traffic sign detection and recognition. However, there are still two problems. First, unlike English traffic signs with only horizontal text, Chinese traffic signs have both horizontal and vertical text. To the best of our knowledge, there is nothing in the literature about simultaneous recognition of both horizontal and vertical text in Chinese text-based traffic signs. Second, most existing methods focus on wild and expressway scenes; few focus on street scenes. To solve these problems, we propose a mixed vertical-and-horizontal-text traffic sign detection and recognition algorithm for street-level scene. First, an effective combination of different red, green and blue components is used to distinguish the traffic signs from many objects of similar color in the very complex street scenes. Second, unlike English letters, the strokes of many Chinese characters are unconnected, which may result in that a character will be detected as two or more characters. Unlike the English text lines, which are only horizontal, the Chinese text lines on text-based traffic signs are usually both in horizontal and vertical directions. Our proposed method uses the position and structural information of the characters to form the text lines. A dataset of Chinese text-based traffic signs is collected. Experimental results indicate the effectiveness of the proposed method. | ||
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10.1109/ACCESS.2020.2986500 doi (DE-627)DOAJ016105257 (DE-599)DOAJ67fd8f8c6f1d4938b9a50f234929dd47 DE-627 ger DE-627 rakwb eng TK1-9971 Jiefeng Guo verfasserin aut Mixed Vertical-and-Horizontal-Text Traffic Sign Detection and Recognition for Street-Level Scene 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Much effort has been dedicated to text-based traffic sign detection and recognition. However, there are still two problems. First, unlike English traffic signs with only horizontal text, Chinese traffic signs have both horizontal and vertical text. To the best of our knowledge, there is nothing in the literature about simultaneous recognition of both horizontal and vertical text in Chinese text-based traffic signs. Second, most existing methods focus on wild and expressway scenes; few focus on street scenes. To solve these problems, we propose a mixed vertical-and-horizontal-text traffic sign detection and recognition algorithm for street-level scene. First, an effective combination of different red, green and blue components is used to distinguish the traffic signs from many objects of similar color in the very complex street scenes. Second, unlike English letters, the strokes of many Chinese characters are unconnected, which may result in that a character will be detected as two or more characters. Unlike the English text lines, which are only horizontal, the Chinese text lines on text-based traffic signs are usually both in horizontal and vertical directions. Our proposed method uses the position and structural information of the characters to form the text lines. A dataset of Chinese text-based traffic signs is collected. Experimental results indicate the effectiveness of the proposed method. Text recognition text-based traffic sign recognition traffic sign detection text boxes Electrical engineering. Electronics. Nuclear engineering Rongxuan You verfasserin aut Lianfen Huang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 69413-69425 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:69413-69425 https://doi.org/10.1109/ACCESS.2020.2986500 kostenfrei https://doaj.org/article/67fd8f8c6f1d4938b9a50f234929dd47 kostenfrei https://ieeexplore.ieee.org/document/9060949/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 69413-69425 |
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Mixed Vertical-and-Horizontal-Text Traffic Sign Detection and Recognition for Street-Level Scene |
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Much effort has been dedicated to text-based traffic sign detection and recognition. However, there are still two problems. First, unlike English traffic signs with only horizontal text, Chinese traffic signs have both horizontal and vertical text. To the best of our knowledge, there is nothing in the literature about simultaneous recognition of both horizontal and vertical text in Chinese text-based traffic signs. Second, most existing methods focus on wild and expressway scenes; few focus on street scenes. To solve these problems, we propose a mixed vertical-and-horizontal-text traffic sign detection and recognition algorithm for street-level scene. First, an effective combination of different red, green and blue components is used to distinguish the traffic signs from many objects of similar color in the very complex street scenes. Second, unlike English letters, the strokes of many Chinese characters are unconnected, which may result in that a character will be detected as two or more characters. Unlike the English text lines, which are only horizontal, the Chinese text lines on text-based traffic signs are usually both in horizontal and vertical directions. Our proposed method uses the position and structural information of the characters to form the text lines. A dataset of Chinese text-based traffic signs is collected. Experimental results indicate the effectiveness of the proposed method. |
abstractGer |
Much effort has been dedicated to text-based traffic sign detection and recognition. However, there are still two problems. First, unlike English traffic signs with only horizontal text, Chinese traffic signs have both horizontal and vertical text. To the best of our knowledge, there is nothing in the literature about simultaneous recognition of both horizontal and vertical text in Chinese text-based traffic signs. Second, most existing methods focus on wild and expressway scenes; few focus on street scenes. To solve these problems, we propose a mixed vertical-and-horizontal-text traffic sign detection and recognition algorithm for street-level scene. First, an effective combination of different red, green and blue components is used to distinguish the traffic signs from many objects of similar color in the very complex street scenes. Second, unlike English letters, the strokes of many Chinese characters are unconnected, which may result in that a character will be detected as two or more characters. Unlike the English text lines, which are only horizontal, the Chinese text lines on text-based traffic signs are usually both in horizontal and vertical directions. Our proposed method uses the position and structural information of the characters to form the text lines. A dataset of Chinese text-based traffic signs is collected. Experimental results indicate the effectiveness of the proposed method. |
abstract_unstemmed |
Much effort has been dedicated to text-based traffic sign detection and recognition. However, there are still two problems. First, unlike English traffic signs with only horizontal text, Chinese traffic signs have both horizontal and vertical text. To the best of our knowledge, there is nothing in the literature about simultaneous recognition of both horizontal and vertical text in Chinese text-based traffic signs. Second, most existing methods focus on wild and expressway scenes; few focus on street scenes. To solve these problems, we propose a mixed vertical-and-horizontal-text traffic sign detection and recognition algorithm for street-level scene. First, an effective combination of different red, green and blue components is used to distinguish the traffic signs from many objects of similar color in the very complex street scenes. Second, unlike English letters, the strokes of many Chinese characters are unconnected, which may result in that a character will be detected as two or more characters. Unlike the English text lines, which are only horizontal, the Chinese text lines on text-based traffic signs are usually both in horizontal and vertical directions. Our proposed method uses the position and structural information of the characters to form the text lines. A dataset of Chinese text-based traffic signs is collected. Experimental results indicate the effectiveness of the proposed method. |
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Mixed Vertical-and-Horizontal-Text Traffic Sign Detection and Recognition for Street-Level Scene |
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