This study proposes a layout-based chunk alignment method (Layout-CA) as an intermediate step between document- and sentence-level parallel text alignment for bilingual document images. Visually rich printed materials, such as institutional reports and magazines, often contain high-quality translations and are valuable sources of parallel data, yet their layout cues are underutilized. Layout-CA aligns semantically coherent text chunks across document pairs by integrating multi-modal cues from textual content and layout, and sentence alignment is then performed within the aligned chunk pairs. Experiments on English UNESCO reports and their Japanese translations show that introducing chunk alignment improves downstream sentence alignment for both Bleualign and Vecalign. When document order is disrupted, Layout-CA preserves alignment coverage by restricting sentence matching to corresponding chunks, enabling robust alignment in multilingual image documents.