DEVELOPMENT OF A NIGERIAN CULTURAL ATTIRE RECOGNITION SYSTEM - OGUNBIYI DIMPLE; JIMOH KUDIRAT; ADEBAYO OLAJIDE; OKELOLA LOVELYN (Journal of Engineering Studies and Research)
This paper presents the development of a system to automatically recognize Nigerian traditional attire worn by major ethnic groups. Samples of clothing images depicting the cultural groups were obtained from publicly available online sources and an architecture to classify the images classes was designed using the Convolutional Neural Network (CNN) model. Performance evaluation results from experiment show that the model can classify images accordingly, achieving a validation accuracy score of 86 %. A web application interface was also implemented to validate the model’s accuracy which shows good potential when integrated in commercial clothing applications.