International Journal of Advanced Research in Computer and Communication Engineering

Abstract: This paper presents an experimental study focused on optimizing Portable Document Format (PDF) file size reduction through the sequential application of multiple online compression tools to achieve user-specified file size targets. Existing online compressors employ distinct algorithms for image re-encoding, font subsetting, and metadata removal, often yielding varied results in terms of compression efficiency and quality preservation, but not to the user-specified size. The proposed approach investigates the cumulative effect of applying multiple compression tools in a defined sequence to achieve enhanced file size reduction without significant quality degradation. A heterogeneous dataset of PDF files, commonly required for uploading as Proof of Address (POA) and Proof of Identity (POI) on Indian government websites, such as Aadhaar Card, PAN Card, and property documents, comprising text-heavy and image-rich content, was compressed using popular online tools, including SmallPDF, iLovePDF, PDFCompressor, and Adobe Acrobat. The performance of each tool and its sequential combinations was evaluated using metrics such as compression ratio, percentage reduction, and visual fidelity indices. Experimental results demonstrate that optimized multi-tool sequences achieved up to 27% greater reduction in file size compared to single-tool compression, while maintaining acceptable readability and structural integrity. The findings highlight the potential of hybrid compression pipelines for efficient ways to compress the files according to the needed file size to upload.

Keywords: PDF compression, multi-tool optimization, hybrid compression pipeline, online compression tools, document size reduction, PSNR, SSIM, digital archiving.

Downloads: | DOI: 10.17148/IJARCCE.2025.141187