Panel Font Blurriness Recognition Dataset

The current industrial sector faces challenges in accurately recognizing characters printed with inkjet technology, especially when they are unclear or misaligned. Existing solutions often struggle with high variability in font styles and printing conditions, leading to misinterpretations that can affect operational efficiency. This dataset aims to address the specific technical challenges in recognizing blurry fonts while ensuring that operational processes remain intuitive. The data is collected using high-resolution cameras in controlled environments, ensuring optimal lighting and focus. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert reviews to ensure high accuracy. The dataset is organized into a structured format with images stored in JPG and associated metadata in a separate JSON file.