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Indonesian traffic sign detection based on Haar-PHOG features and SVM classification

Aris Sugiharto
Aris Sugiharto
, 
Agus Harjoko
Agus Harjoko
 e 
Suharto Suharto
Suharto Suharto
   | 05 ott 2020
International Journal on Smart Sensing and Intelligent Systems's Cover Image
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Article Category: Research-Article
Pubblicato online: 05 ott 2020
Pagine: 1 - 15
Ricevuto: 03 giu 2020
DOI: https://doi.org/10.21307/ijssis-2020-026
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© 2020 Aris Sugiharto et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1:

Proposed research stages.
Proposed research stages.

Figure 2:

Segmentation and morphology.
Segmentation and morphology.

Figure 3:

Wavelet discrete transform.
Wavelet discrete transform.

Figure 4:

Haar–PHOG on each sub-band of wavelet.
Haar–PHOG on each sub-band of wavelet.

Figure 5:

The whole Haar–PHOG feature.
The whole Haar–PHOG feature.

Figure 6:

Data training and testing.
Data training and testing.

Figure 7:

Interface detection on traffic signs.
Interface detection on traffic signs.

Figure 8:

Comparison of accuracy value between HOG, PHOG, and Haar–PHOG features.
Comparison of accuracy value between HOG, PHOG, and Haar–PHOG features.

Figure 9:

Comparison of precision value between HOG, PHOG, and Haar–PHOG features.
Comparison of precision value between HOG, PHOG, and Haar–PHOG features.

Figure 10:

Comparison of recall value between HOG, PHOG, and Haar–PHOG features.
Comparison of recall value between HOG, PHOG, and Haar–PHOG features.

Confusion matrix of Semarang-Solo road.

Haar–PHOG
HOG PHOG LL LL HL LH LL HL LH HH
Semarang-Solo Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes)
Actual (No) 1,896 232 1,807 172 1,881 161 1,865 145 1,868 145
Actual (Yes) 27 867 116 927 42 938 58 954 55 954

Confusion matrix of Semarang-Yogyakarta road.

Haar–PHOG
HOG PHOG LL LL HL LH LL HL LH HH
Semarang-Yogyakarta Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes)
Actual (No) 2,492 132 2,356 144 2,471 84 2,451 56 2,451 52
Actual (Yes) 59 797 195 785 80 845 100 873 100 877

Confusion matrix of Semarang-Salatiga toll road.

Haar–PHOG
HOG PHOG LL LL HL LH LL HL LH HH
Semarang-Salatiga toll Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes)
Actual (No) 1,504 123 1,421 162 1,427 103 1,433 79 1,431 73
Actual (Yes) 13 859 96 820 90 879 84 903 86 909

Comparison of precision HOG, PHOG, and Haar–PHOG features.

Precision (%)
HOG PHOG Haar–PHOG
Road Fleyeh (2015) LL LL HL LH LL HL LH HH
Solo-Yogyakarta 90.55 90.29 95.14 96.70 96.44
SMG-Yogyakarta 85.79 84.50 90.96 93.97 94.40
SMG-Solo 78.89 84.35 85.35 86.81 86.81
SMG-SLTG-Toll 87.47 83.50 89.51 91.96 92.57

Comparison of accuracy HOG, PHOG, and Haar–PHOG features.

Accuracy (%)
HOG PHOG Haar–PHOG
Road Fleyeh (2015) LL LL HL LH LL HL LH HH
Solo-Yogyakarta 95.99 92.63 97.18 97.44 97.24
SMG-Yogyakarta 94.51 90.26 95.29 95.52 95.63
SMG-Solo 91.43 90.47 93.28 93.28 93.38
SMG-SLTG-Toll 94.56 89.68 92.28 93.48 93.64

Testing time of HOG, PHOG, and Haar–PHOG features.

Testing time (milliseconds)
Haar–PHOG
Road HOG PHOG LL LL HL LH LL HL LH HH
Solo-Yogyakarta 18.40 3.90 3.00 4.50 5.00
SMG-Yogyakarta 19.00 4.40 2.60 4.40 5.00
SMG-Solo 19.50 4.00 2.60 4.40 5.10
SMG-SLTG-TOLL 19.80 4.00 2.80 4.60 5.30
Average 19.18 4.08 2.75 4.48 5.10

Composition of training and testing data.

Training data (ROI)
Road Positive Negative Testing data (frame) Number of traffic sign
Solo-Yogyakarta 1,500 1,500 1,100 1,153
Semarang-Yogyakarta 1,500 1,500 950 929
Semarang-Solo 1,500 1,500 1,000 1,099
Semarang – Salatiga Toll Roads 1,500 1,500 950 982

Comparison of recall HOG, PHOG, and Haar–PHOG features.

Recall (%)
HOG PHOG Haar–PHOG
Road Fleyeh (2015) LL LL HL LH LL HL LH HH
Solo-Yogyakarta 97.03 87.63 96.23 95.54 95.21
SMG-Yogyakarta 93.11 80.10 91.35 89.72 89.76
SMG-Solo 96.98 88.88 95.71 94.27 94.55
SMG-SLTG-Toll 98.51 89.52 90.71 91.49 91.36

Range of hue and saturation threshold values.

Color Hue Saturation
Red H ≥ 290 or H ≤ 15 S ≥ 10
Yellow 20 ≤ H ≤ 65 S ≥ 150
Green 180 < H ≤ 280 S ≥ 10

Confusion matrix of Solo-Yogyakarta road.

Haar–PHOG
HOG PHOG LL LL HL LH LL HL LH HH
Solo-Yogyakarta Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes) Predict (No) Predict (Yes)
Actual (No) 2,328 109 2,213 112 2,317 56 2,308 38 2,304 41
Actual (Yes) 32 1,044 147 1,041 43 1,097 52 1,115 56 1,112

The training time of HOG, PHOG, and Haar–PHOG features.

Training time (sec)
Haar–PHOG
Road HOG PHOG LL LL HL LH LL HL LH HH
Solo-Yogyakarta 148.38 512.66 15.73 27.31 32.78
SMG-Yogyakarta 148.02 555.50 16.25 27.05 32.59
SMG-Solo 168.98 537.25 15.73 28.73 33.66
SMG-SLTG-Toll 165.03 583.41 18.06 32.05 35.61
Average 157.60 547.20 16.45 28.79 33.66
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