Smart Clothing Self-Checkout Mirror with Hand Landmark Detection and YOLOv11

Even with the rise of e-commerce and fast shipping, nothing compares to the joy of physically trying on a garment before purchasing. This paper aims to enhance the shopping experience by reducing paper waste and streamlining the process of buying garments. The study introduces a smart self-checkout system powered by an object detection model based on YOLOv11, enabling accurate and real-time identification of clothing items. A sample custom dataset featuring school uniforms was developed to train the model. The application integrates this model with a hand landmark detection system, replacing traditional touchscreens to facilitate user interaction. Additionally, the system supports payments through LINE Pay, allowing users to complete transactions conveniently and efficiently. This system not only enhances user convenience but also promotes a more sustainable shopping experience.