Automatic Identification of a Playing Card through Knn Using a Raspberry Pi 3

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.