TFIC: End-to-End Text-Focused Image Compression for Coding for Machines

• URL: http://arxiv.org/abs/2503.19495v1
• Date: Tue, 25 Mar 2025 09:36:13 GMT
• Title: TFIC: End-to-End Text-Focused Image Compression for Coding for Machines
• Authors: Stefano Della Fiore, Alessandro Gnutti, Marco Dalai, Pierangelo Migliorati, Riccardo Leonardi,
• Abstract summary: We present an image compression system designed to retain text-specific features for subsequent Optical Character Recognition (OCR)<n>Our encoding process requires half the time needed by the OCR module, making it especially suitable for devices with limited computational capacity.
• Score: 50.86328069558113
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Traditional image compression methods aim to faithfully reconstruct images for human perception. In contrast, Coding for Machines focuses on compressing images to preserve information relevant to a specific machine task. In this paper, we present an image compression system designed to retain text-specific features for subsequent Optical Character Recognition (OCR). Our encoding process requires half the time needed by the OCR module, making it especially suitable for devices with limited computational capacity. In scenarios where on-device OCR is computationally prohibitive, images are compressed and later processed to recover the text content. Experimental results demonstrate that our method achieves significant improvements in text extraction accuracy at low bitrates, even improving over the accuracy of OCR performed on uncompressed images, thus acting as a local pre-processing step.

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