Test Automation for Symbol Recognition on the Map
2023 31ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU(2023)
Abstract
In this study, various machine learning and image analysis approaches such as Template Matching, HOG, SVM, Faster RCNN and YOLO are examined and compared for the symbol recognition problem in color maps. Some difficulties were identified regarding the forms of the symbols, the complexity of the maps or the placement of the symbols on the map. Observations about the success or failure of the methods against the difficulties defined according to the experiments are presented. It has been observed that methods involving artificial neural networks are more successful when performing symbol recognition on color maps. The highest result was obtained with Faster RCNN as 91%.
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Key words
Symbol Recognition,Feature Extraction,Support Vector Machines,Template Matching,Convolutional Neural Network,Object Detection,Software Testing
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