Machine Recognition of Map Point Symbols Based on Yolov3 and Automatic Configuration Associated with POI

Bibliographic Data

ID22034889
AuthorsHuili Zhang (0000-0001-8403-4694, Zhengzhou University), Xiaowen Zhou (0009-0009-5774-0265, Zhengzhou University), Huan Li (0000-0003-0910-1433, Zhengzhou University), Ge Zhu (0000-0002-2109-4857, Zhengzhou University), Hongwei Li (0000-0001-5682-9780, Zhengzhou University, corresponding author)
Year2022
Volume11
Issue11
Pages540
Publication date2022-10-28
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi11110540
OpenAlexW4307939081
LanguageEN
Citations received1
References cited48

This study is oriented towards machine autonomous mapping and the need to improve the efficiency of map point symbol recognition and configuration. Therefore, an intelligent recognition method for point symbols was developed using the You Only Look Once Version 3 (YOLOv3) algorithm along with the Convolutional Block Attention Module (CBAM). Then, the recognition results of point symbols were associated with the point of interest (POI) to achieve automatic configuration. To quantitatively analyze the recognition effectiveness of this study algorithm and the comparison algorithm for map point symbols, the recall, precision and mean average precision (mAP) were employed as evaluation metrics. The experimental results indicate that the recognition efficiency of point symbols is enhanced compared to the original YOLOv3 algorithm, and that the mAP is increased by 0.55%. Compared to the Single Shot MultiBox Detector (SSD) algorithm and Faster Region-based Convolutional Neural Network (Faster RCNN) algorithm, the precision, recall rate, and mAP all performed well, achieving 97.06%, 99.72% and 99.50%, respectively. On this basis, the recognized point symbols are associated with POI, and the coordinate of point symbols are assigned through keyword matching and enrich their attribute information. This enables automatic configuration of point symbols and achieves a relatively good effect of map configuration

Algorithm · Computer vision · Convolutional neural network · Precision and recall · Recall · Advanced Image and Video Retrieval Techniques · Computer Science · Handwritten Text Recognition Techniques · Image Retrieval and Classification Techniques · Mathematics · Artificial Intelligence

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Open DOIOpen Access