Abstract
Traditional food knowledge (TFK) is an essential aspect of human life. In terms of sociocultural aspects, TFK is necessary to protect ancestral culture. In terms of health, traditional foods contain better and more natural ingredients compared to the ingredients of processed foods. Considering this background, in this study, data acquisition and automatic food recognition were performed for traditional food in Indonesia. The food images were captured in a professional mini studio. The food image data were captured under the same light intensity, camera settings, and shooting distance from the camera. The parameters were precisely measured and configured with a light intensity meter, adjustable lighting, and a laser distance measurement device. The data of 1644 traditional food images were successfully obtained in the data acquisition process. These images corresponded to 34 types of traditional foods, and 30–50 images were obtained for each type of food. The size of the raw food image data was 53 GB. The data were divided into sets for training, testing, and validation. An automatic recognition system was developed to classify the traditional food of Indonesia. Training was performed using several types of convolutional neural network (CNN) models such as Densenet121, Resnet50, InceptionV3, and Nasnetmobile. The evaluation results indicated that when using a high quality dataset, the automatic recognition system could realize satisfactory area under the receiver operating characteristics (AUROC) and high accuracy, precision, and recall values of more than 0.95.
Highlights
Traditional food knowledge is the collective cultural wisdom of food systems that is passed down through generations [1]
Traditional food knowledge helps in maintaining cultural diversity and ensuring food security for the community [1]
Our evaluation indicated that multipath-based convolutional neural network (CNN) (Densenet-121) can achieve a higher area under the receiver operating characteristics (AUROC) compared to that of the depth-based CNN (Inception-V3)
Summary
Traditional food knowledge is the collective cultural wisdom of food systems that is passed down through generations [1]. The sociocultural, economic, and health aspects of a specific ethnic group of a specific region can be inferred based on the traditional food knowledge. Traditional food knowledge helps in maintaining cultural diversity and ensuring food security for the community [1]. According to Sharif, the cultural identity of an ethnic community or region corresponds to the Wibisono et al J Big Data (2020) 7:69 traditional food [3]. Traditional food represents the cultural diversity of a region, as it uniquely represents each ethnic community within the region. It is essential to preserve the traditional food knowledge to maintain the diversity of the region. Localizing the food systems can support the local food suppliers in the agricultural sector and boost the economy of the region
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