TFIC: End-to-End Text-Focused Image Compression for Coding for Machines
Journal:
arXiv
Published Date:
Mar 25, 2025
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.
