10 Ways to Improve Capture OCR and Indexing
The recognition phase of capture may seem to be the most important step relevant to automated indexing – since it is, after all, the phase where OCR is performed. But at least half of the factors relevant to successful indexing occur during the pre-recognition steps, particularly in obtaining appropriate image quality for OCR and indexing.
Doculabs blog is one of my favorites and Rich Medina, Co-Founder and Principal Consultant at Doculabs Inc. has done an excellent job of summarizing how to maximize implementing Optical Character Recognition (OCR) in your organization.
It is one thing to have great scanner speed and the Inside Sales Team at ImageSource is a great resource to help you find the right scanners for your organization. However, organizations need to also focus on how much manual data entry they are doing, error corrections, and re-scanning, as these can have dramatic impacts on the overall capture time. The goal of every one of our customers is to improve processes, reducing time and labor involved with processing, accessing, and handling information within their organization. There is a strong possibility of reducing overall operating expenses by using OCR to automatically extract information and to auto index.
I encourage you to read this Doculabs blog as it is extremely pertinent for organizations that already have OCR implemented or for those just beginning to think about implementing OCR.