一种面向交通标志识别系统的图像识别算法

doi:10.16180/j.cnki.issn1007-7820.2019.07.012

Abstract

Abstract:

Most of the machine algorithms for the traffic sign recognition system have problems of high computational complexity and poor real-time performance. Hence, based on the ELM model and the improved PCA method, an image recognition algorithm called PCA-ELM for the traffic sign recognition system was proposed. With the help of the extraction of HOG features, dimensionality reduction of improved PCA method, and the feature training of ELM model, the algorithm could realize the recognition of traffic sign images. Being tested and compared, it was found that the PCA-ELM algorithm had high recognition rate with suitable or even lower computational complexity, which well meets the accuracy and real-time requirements of image recognition for the traffic sign recognition system and had certain practical value.

Key words: traffic sign, image recognition, HOG, PCA, ELM

CLC Number:

TP393

ZHANG Changqing,YANG Nan. An Image Recognition Algorithm for Traffic Sign Recognition System[J].Electronic Science and Technology, 2019, 32(7): 60-64.

Figures/Tables 5

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Table 1

References 16

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方法	Mandatory/%	Derestriction/%	Unique/%	Danger/%	Total/%
PCA-ELM	99.81	94.01	99.88	96.74	97.78
Committee of CNNs	99.91	99.63	99.13	98.99	99.39
Multi-scale CNNs	97.17	94.50	98.65	98.11	98.28
LDA on HOG 2	97.15	86.77	98.71	93.69	95.73
2LDA+5SVM	96.98	99.73	99.45	94.18	96.44

An Image Recognition Algorithm for Traffic Sign Recognition System

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