Efficient Real-time Book Cover Text Extraction with YOLOv8 and SpaCy

In this paper, we explore the integration of advanced image processing and natural language processing (NLP) techniques to extract textual content from book cover images. Our approach leverages YOLOv8 for accurate text localization, Pytesseract for optical character recognition (OCR) to digitize text regions, and spaCy for deep NLP analysis, aiming to detect text comprehensively. The study is grounded in a dataset of 306 varied book cover images, meticulously compiled to train and evaluate our model's effectiveness across a spectrum of design aesthetics. The YOLOv8 model demonstrated a remarkable precision rate of 91.2