Abstract

This academic work has the main objective to develop a system for automatic recognition of an English playing card located on a table using computer vision techniques for capturing, preprocessing, and segmenting the image independently of the orientation and the depression angle. The algorithm used as a classifier to recognize the card is k-nearest neighbor (kNN). At training stage, a set based on a list of alphanumeric characters was used. The result of the classification was sent to an audio output using a converter from text to voice. This algorithm was implemented in an embedded system Raspberry Pi 3 under the operative system Raspbian Jessie. The system developed has an accuracy of 95% and an average wait-response of 5 seconds taking into account the audio playing.
Translated title of the contributionIdentificación automática de una tarjeta de juego a través de Knn Uso de una Raspberry Pi 3
Original languageEnglish (US)
StatePublished - Nov 2016
EventInternational Conference on Information Systems and Computer Science - Quito, Ecuador
Duration: 24 Nov 201626 Nov 2016

Conference

ConferenceInternational Conference on Information Systems and Computer Science
Abbreviated titleINCISCOS 2016
CountryEcuador
CityQuito
Period24/11/1626/11/16

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    Tufiño Cardenas, R. E., & Ortega Martinez, H. R. (2016). Automatic Identification Of A Playing Card Through Knn Using A Raspberry Pi 3. Paper presented at International Conference on Information Systems and Computer Science, Quito, Ecuador.