Digital forensics plays a pivotal role in uncovering crucial evidence from electronic devices, with Optical Character Recognition (OCR) standing out as a key technology for extracting text from images. This paper explores the challenges associated with OCR, including image quality, font variations, and contextual understanding. Despite its invaluable utility, the renowned digital forensics tool Autopsy currently lacks an inbuilt text extraction facility, presenting an opportunity for innovation. In response to this gap, our proposed novelty suggests integrating a dedicated text extraction module within Autopsy. While Autopsy excels in keyword searches, the addition of a text extraction feature would provide investigators with a comprehensive solution for analyzing textual content within digital image media. This paper concludes by emphasizing the significance of combining OCR with advanced forensic tools and highlights how enhancing Autopsy's capabilities aligns with the evolving demands of the digital forensic landscape. The suggested innovation positions Autopsy as a more robust and holistic tool, ensuring forensic practitioners can effectively navigate the complexities of digital evidence analysis. The open-source developed tool is available at: https://digital-forensics-text-vision.netlify.app/.