Guide Sign Analysis of Traffic Sign Data-Set Using Supervised Spiking Neuron Technique
Keywords:SNN, traffic sign, hidden region, brightness, rotation, mean error, detection, recognition.
In this paper, 20 guided traffic signs mostly displayed around Malacca area were selected as project databased. Early hypothesis was made as the error for each usable image will increased as more interference introduced to the original image used. Three types of conditions which are hidden region, image brightness and image rotation were selected as an experiment to analyze the performance of each sign used. Each condition will perform a specific error to generate their mean value and in the same, image recognition will take place in the matchup process. By focusing on the result, it produces hidden region critically ascending mean error value at 62.5% = 0.07 and has average value at others points. For image brightness effect, it shows a higher mean error value collected at less brightness points and non-stable pattern at 10% to 60% brightness. As for rotation upshot, the values show a critically ascending for error value at 22.5% and slightly increase at 2% to 5% rotation point. For the recognition process, at 6.25% hidden region, almost 70% of images are correctly matched to its own classes while at 62.5% hidden region only 40% of images are correctly matched to its own classes and leaving 2 images to outperform. For -40% brightness, 45% of images are correctly matched to its own classes while at 60% brightness 65% of images are correctly matched to its own classes and leaving 1 image to outperform. Lastly, at 2.5 degree rotation, 85% of images are correctly matched to its own classes while at 25° rotation, 45% of images are correctly matched to its own classes and leaving 2 images to outperform. Finally, the error forms will affect the final output response of the detected traffic signs used.
 B. Meftah, O. LÃ©zoray, S. Chaturvedi, A. A. Khurshid, and A. Benyettou, â€œImage processing with spiking neuron networks,â€ Stud. Comput. Intell., vol. 427, (2013), pp. 525â€“544.
 S. Bohte (2003), Spiking neural networks.
 A. GrÃ¼ning and S. M. Bohte, â€œSpiking Neural Networks: Principles and Challenges,â€ Elen.Ucl.Ac.Be, no. April, pp. 23â€“25, 2014.
 Eugene M. Izhikevich â€œSimple Model of Spiking Neuronsâ€ (PDF).Vol 14, No. 6, Dated December 2003.
 M. M. Lau, K. H. Lim, and A. A. Gopalai, â€œMalaysia traffic sign recognition with convolutional neural network,â€ 2015 IEEE Int. Conf. Digit. Signal Process, (2015), pp. 1006â€“1010.
 N Mohd Ali, MS Karis, SA Ahmad Tarusan, Gao-Jie Wong, MS Mohd Aras, MB Bahar, AF Zainal Abidin, â€œInspection and Quality Checking of Ceramic Cup using Machine Vision Technique: Design and Analysisâ€, Jurnal Teknologi, (2017), pp. 33-38.
 N Mohd Ali, MS Karis, NM Mohd Sobran, MB Bahar, Oh Kok Ken, M Mat Ibrahim, NF Johan, â€œDetection of Multiple Mangoes using Histogram of Oriented Gradient Technique in Aerial Monitoringâ€, ARPN Journal of Engineering and Applied Sciences, (2017), pp. 2730-2736.
 MS Karis, N Mohd Ali, A Mohd Basar, HI Jaafar, AF Zainal Abidin, â€œAn Analysis on out-of-plane Face Detection among Female Student and Illumination effects using SIFT and SUFTâ€, AIP Conference Proceedings, (2016).
 MS Karis, N Mohd Ali, WH Mohd Saad, AF Zainal Abidin, N Ismaun, M Abd Aziz, â€œPerformance Analysis between Keypoints of SURF and Skin Colour YCBCR based Technique for Face Detection among Final Year UTeM Male Studentâ€, Jurnal Teknologi (2017), pp. 65-69.
 N Mohd Ali, MS Karis, AF Zainal Abidin, B Bakri, NR Abd Razif, â€œTraffic Sign Detection and Recognition: Review and Analysisâ€, Jurnal Teknologi, (2017), pp. 107-113.
 Mohamed N, Voon WS, Hashim HH, Othman I (2011), An overview of road traffic injuries among children in Malaysia and its implication on road traffic injury prevention strategy. https://www.researchgate.net/profile/Hizal_Hanis_Hashim/publication/312771185_Research_report_an_overview_of_road_traffic_injuries_among_children_in_Malaysia_and_its_implication_on_road_traffic_injury_prevention_strategy/links/5a8508db4585159152b814ea/Research-report-an-overview-of-road-traffic-injuries-among-children-in-Malaysia-and-its-implication-on-road-traffic-injury-prevention-strategy.pdf.