Abstract
Pattern recognition is a mature but exciting and fast-developing field concerning computer vision, image processing, shape drawing, and text analysis. The shape pattern can be recognised easily using this technique. Some children have difficulties in identifying shapes. Therefore, through shape drawing exercises, it helps children to understand better. This project aims to develop a mobile application, assisting children in practising drawing using pattern recognition. It can identify shape types by matching the shape pattern with the given input. It will classify the information provided based on the feature extraction using the Freeman Chain Code. Then, each shape pattern is recognised using regular expression tools. Functionality testing has been conducted on this application with an accuracy of 80%. The application will encourage children to draw more by giving feedback on the exercise that they do. It may assist children in learning a new, better way of drawing shape accurately while improving children’s fine motor skills.
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References
Romano E, Babchishin L, Marquis R, Fréchette S (2015) Childhood maltreatment and educational outcomes. Trauma Violence Abuse 16(4):418–437
Resnick I, Verdine BN, Golinkoff R, Hirsh-Pasek K (2016) Geometric toys in the attic? A corpus analysis of early exposure to geometric shapes. Early Childh Res Q 36:358–365
Verdine BN, Zimmermann L, Foster L, Marzouk MA, Roberta MG, Pasek KH, Newcombe N (2019) Effects of geometric toy design on parent–child interactions and spatial language. Early Child Res Q 46:126–141
Krig S (2014) Image pre-processing. In: Krig S (ed.) Computer vision metrics: survey, taxonomy, and analysis, pp. 39–83. Apress, Berkeley
Nixon M, Aguado A (2020) Feature extraction and image processing for computer vision, 4th edn. Academic Press of Elsevier, London
Ansari S (n.d.). https://www.geeksforgeeks.org/pattern-recognition-introduction/
Pistono F (2016). https://medium.com/@FedericoPistono/on-the-importance-of-pattern-recognition-6d7573d43595
Rouse M, Ansari S (n.d.). Retrieved from https://whatis.techtarget.com/definition/pattern-recognition
Brownlee J (2016). https://machinelearningmastery.com/supervised-and-unsupervised-machine-learning-algorithms/
Althobaiti H, Lu C (2017) A survey on Arabic optical character recognition and an isolated handwritten Arabic Character Recognition algorithm using encoded freeman chain code. In: Proceeding of 51st annual conference on information sciences and systems (CISS), Baltimore, MD, pp 1–6
Baji F, Mocanu M (2018) Chain code approach for shape based image retrieval. Ind J Sci Technol 11(3):1–17
Annapurna P, Kothuri S, Lukka S (2013) Digit recognition using Freeman chain code. Int J Appl Innov Eng Manag (IJAIEM) 2(8):2319–4847
Xia LY, Dai SG (2013) Circle and circular arc detection algorithm research based on Freeman chain code. In: IEEE 4th international conference on electronics information and emergency communication, Beijing, pp 230–233
Azmi AN, Nasien D (2014) Feature vector of binary image using Freeman chain code (FCC) representation based on structural classifier. Int J Adv Soft Comput Appl 6(2):30–35
Husain NH, Diah NM, Hanum HM (2017) The relevance of Freeman Chain Code for copying activities. In: 2017 IEEE conference on e-learning, e-management and e-services (IC3e), Miri, Serawak, pp 138–144
Azmi AN, Nasien D, Omar FS (2016) Biometric signature verification system based on Freeman chain code and k-nearest neighbor, Multimed Tools Appl 76:1–15
Liu P, Zhang J, Guo K (2015) A parking-lines recognition algorithm based on Freeman Chain Code. In: Proceeding of 7th international conference on intelligent human-machine systems and cybernetics, Hangzhou, pp 349–352
Acknowledgements
The authors would like to thank Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, for sponsoring this research.
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Jen, J.A., Diah, N.M., Ibrahim, Z. (2021). Drawing and Recognising Simple Shapes with Real-Time Feedback Using Pattern Recognition. In: Alfred, R., Iida, H., Haviluddin, H., Anthony, P. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 724. Springer, Singapore. https://doi.org/10.1007/978-981-33-4069-5_8
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