Making a PDF’s Images Searchable for RAG, Without Paying to Read Them All

Making PDF images searchable for RAG systems can be managed efficiently using a cost-ordered cascade to avoid expensive, unnecessary analysis. An initial, free filter first removes the majority of images that have no search value, such as logos, decorative lines, or icons, by checking their size, shape, and repetition. The few remaining images are then classified into types like 'text' or 'chart' using simple pixel analysis, not a costly model. This classification determines the next step: simple text images are sent to cheap, classic OCR, while only complex visuals like charts or photos are processed by an expensive vision model. This strategic, tiered approach dramatically cuts costs by ensuring that powerful AI is only used on the small fraction of images containing valuable information.