Arbitrary shape text detection method based on Fourier centerline prediction

Fig. 4. Comparison of the detection quality of the method in this paper with TextRay^［11］， ABCNet^［12］， TESTR^［6］ and DPText^［7］ on selected challenging images from the CTW1500 dataset. Among them， TESTR and DPText are the latest Transformer-based methods.

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Table 1. Ablation experiments
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Table 1. Ablation experiments
TCR ASF CTW1500
P/% R/% F/%
- - 75.2 69.6 72.3
- √ 77.4 75.9 76.6
√ - 83.0 70.9 76.5
√ √ 87.3 80.1 83.6

Table 2. Verification of the generalization ability using different amounts of training data on the CTW1500 dataset
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Table 2. Verification of the generalization ability using different amounts of training data on the CTW1500 dataset
数据算法 P/% R/% F/%
50% TextRay^［11］ 75.5 77.8 76.6
ABCNet^［12］ 71.1 80.6 75.6
FCPNet 81.8 75.4 78.5
25% TextRay^［11］ 67.9 74.9 71.2
ABCNet^［12］ 70.0 75.5 72.7
FCPNet 78.5 70.8 74.5

Table 3. Validation of generalization ability using different datasets

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Table 3. Validation of generalization ability using different datasets

方法	CTW1500→TotalText			TotalText→CTW1500
方法	P/%	R/%	F/%	P/%	R/%	F/%
CTD-TLOC^［13］	42.5	25.9	32.2	37.4	50.5	43.0
TFE-PRPA-BCTS^［14］	55.5	31.0	39.8	35.1	57.8	43.6
SADA（Res50-FPN）^［8］	57.1	32.6	41.5	36.7	56.2	44.4
FCPNet	55.5	35.9	43.6	46.5	58.9	51.9

Table 4. Comparison of related methods on CTW1500 and TotalText dataset

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Table 4. Comparison of related methods on CTW1500 and TotalText dataset

方法	Ext.	CTW1500				TotalText
方法	Ext.	P/%	R/%	F/%	FPS	P/%	R/%	F/%	FPS
FCPNet	✕	87.3	80.1	83.6	15.4	89.0	75.0	81.4	12.6
TextSnake^［15］	✓	85.3	67.9	75.6	1.1	82.7	74.5	78.4	1.1
TextField^［3］	✓	79.8	83.0	81.4	6	81.2	79.9	80.6	6
SAST^［16］	✓	81.2	81.7	81.5	27.6	85.6	75.5	80.2	-
PSENet^［17］	✓	79.7	84.8	82.2	3.9	78.0	84.0	80.9	3.9
TextRay^［11］	✓	80.4	82.8	81.6	-	83.5	77.9	80.6	-
ABCNet^［12］	✓	78.5	84.4	81.4	17.9	-	-	78.4	17.9
PSENet^［17］	✕	75.6	80.6	78.0	3.9	81.8	75.1	78.3	3.9
ATRR^［18］	✕	80.2	80.2	80.1	10	80.9	76.2	78.5	10
TFE-PRPA-BCTS^［14］	✕	82.5	81.8	82.2	-	83.5	74.7	78.9	-

Table 5. Performance comparison on the subset of highly curved text instances
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Table 5. Performance comparison on the subset of highly curved text instances
方法 P/% R/% F/%
TextRay^［11］ 85.1 67.2 75.1
ABCNet^［12］ 88.3 62.6 73.2
TESTR^［6］ 86.5 71.7 78.4
DPText^［7］ 92.4 69.3 79.2
FCPNet 83.6 76.3 79.8

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Kun BAI, Zhe WANG, Long MA, Yao XUE, Guodong LI, Tian YAN, Xiaotian WANG. Arbitrary shape text detection method based on Fourier centerline prediction[J]. Chinese Journal of Liquid Crystals and Displays, 2025, 40(6): 905

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