Most software still ‘finds’ data by using the document corners as locator points, rather than ‘fiducials’, which is a better option. It is therefore key to crop the image to capture the area that just represents the document.īad cropping can cause problems with locating data on forms. Documents with a significant black background as illustrated on the first image below, impact any further use of the image. Depending on the scanning application, a black border may or may not be required. The image needs to be straightened so that the sides of the document are parallel to the edge of the output image. The images need to be straightened (or deskewed) to be used for future processes like automated recognition of text, handwriting or check marks. Read on for details about how Perfect Page enhances images for many of the most common, and most challenging, types of scanning applications.ĭeskew and auto-cropping: Incoming mail rarely arrives in a neatly organized stack, especially when documents are mixed in size. When you’re considering your next scanner investment, make sure to take into account all of the ways the right technology could help your business save time, reduce costs and improve accuracy for your scanning operations. All of the features covered in the remainder of this guide are core to Perfect Page technology. Perfect Page technology provides state-of-the-art capabilities for image enhancement, even for very challenging documents and mixed document batches. Kodak Alaris has a strong heritage in image science that focuses on un-paralleled image quality for all kinds of documents. The goal of the Kodak Alaris Advanced Image Processing team is to completely eliminate document preparation over time. That’s a significant manual effort that slows down operations and adds costs that could easily be avoided. The typical, surprising, workaround for this problem? Scan operators use a copier to reprint the document with the contrast set to high. This results in a rescan, or the requirement to conduct manual indexing or data extraction. If it’s just left in the regular flow of documents without image enhancement, quality control checks tend to reject them. ![]() When a hard-to-read document is found in a job, it’s scanned in a separate batch with different settings, often at a higher resolution, which results in unnecessarily large file sizes or increased background noise levels. The right scanners can do this work automatically, saving the labor cost of extra work.įurther, there is even more manual work involved in separating out documents that are considered challenging. Often, operations have staff spend time manually sorting documents by these attributes, instead of putting technology to work for them. Even in a scanning operation that is set-up to process the same document type, such as an invoice - challenges abound: operators are faced with a multitude of different paper types and document sizes, as well as documents which contain different colored backgrounds or a mix of landscape and portrait orientation. It’s not uncommon in a scanning environment to find half (or more) of staff focusing on pre-sorting and preparing documents. Scanning itself is a small part of the digitization process. Document preparation is a major bottleneck
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