Scene Text Detection Algorithm Based on Color Clustering of Textual Pixels

Min Li; Jianbin Zheng; Enqi Zhan; Yang Wang

doi:10.3788/LOP56.071006

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 7 >Page 071006 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 7, 071006 (2019)

Scene Text Detection Algorithm Based on Color Clustering of Textual Pixels

Min Li, Jianbin Zheng, Enqi Zhan^*, and Yang Wang

Author Affiliations

College of Information Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China

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DOI: 10.3788/LOP56.071006 Cite this Article Set citation alerts

Min Li, Jianbin Zheng, Enqi Zhan, Yang Wang. Scene Text Detection Algorithm Based on Color Clustering of Textual Pixels[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071006 Copy Citation Text

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Fig. 1. Flow chart of proposed method

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Color stratification process. (a) Original image; (b) distribution of all pixels in RGB space; (c) robust textual pixels; (d) distribution of only textual pixels in RGB space; (e) clustering results of textual pixels

Fig. 2. Color stratification process. (a) Original image; (b) distribution of all pixels in RGB space; (c) robust textual pixels; (d) distribution of only textual pixels in RGB space; (e) clustering results of textual pixels

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Fig. 3. Schematic of dangle feature

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Fig. 4. Comparison of color stratification results before and after grouping. (a) Original image; (b) image before improvement; (c) image after improvement

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Fig. 5. Flow chart of multi-scale color clustering algorithm

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Fig. 6. Original images and color stratification results. (a) Images with simple background; (b) images with complex background;(c) images with low contrast

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Fig. 7. Comparison of color stratification results by different methods. (a) Original image; (b) proposed method; (c) method in Ref. [6]; (d1) result when d=24 in Ref. [10]; (d2) result when d=56 in Ref. [10]

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Fig. 8. Partial text detection results

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Fig. 9. Partial images under detection failure. (a) Influence of illumination; (b) text occlusion

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Constraint	Definition	Thresholdrange
Height ratio	H_r=height(R₁)/height(R₂)	(0.25,4)
Width ratio	W_r=width(R₁)/width(R₂)	(0.25,4)
Angle	A_angle=arctan(R_h/R_w)	[0,30)
Centroiddistance	d_c= $\begin{matrix} \frac{sqrt (R_{h}^{2} + R_{w}^{2})}{\max [widt h (R_{1}), widt h (R_{2})]} \end{matrix}$	[0,2]
Colordistance	D_color=sqrt $\begin{matrix} [\sum_{C = {r, g, b}} (C_{1} - C_{2})^{2}] \end{matrix}$	[0,30)

Table 1. Constraint conditions for merging in text lines

Method	R	P	f
Proposed method	0.71	0.82	0.76
Method in Ref. [10]	0.68	0.82	0.75
Method in Ref. [13]	0.68	0.86	0.76
Method in Ref. [14]	0.69	0.81	0.75
Method in Ref. [15]	0.65	0.84	0.73

Table 2. Performance comparison of different methods on ICDAR2011 database

Method	R	P	f
Proposed method	0.73	0.82	0.77
Method in Ref. [10]	0.70	0.84	0.76
Method in Ref. [16]	0.65	0.84	0.73
Method in Ref. [17]	0.68	0.79	0.73
Method in Ref. [18]	0.63	0.85	0.72

Table 3. Performance comparison of different methods on ICDAR2013 database

Min Li, Jianbin Zheng, Enqi Zhan, Yang Wang. Scene Text Detection Algorithm Based on Color Clustering of Textual Pixels[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071006

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