Optical Character Recognition (OCR) is a technology that converts the text of various physical documents into digital data using sophisticated pattern recognition techniques and machine learning algorithms. This data and the image of the scanned document can then be combined and stored in databases. Various EDM or ECM systems can then make these documents available to their users. Thanks to OCR, companies can streamline workflows and reduce manual tasks, saving time and money.
WHY IS OCR USEFUL?
The process of scanning content usually results in a digital image that renders the text unsearchable and non-editable. Consequently, storing and using this data requires manual entry, a process that is both time-consuming and labor-intensive. OCR technology eliminates this need by automatically converting scanned images into digital text, ready for immediate integration into business systems. This not only reduces the errors associated with manual data entry but also significantly enhances efficiency. By streamlining document handling and processing, OCR allows companies to focus on more critical tasks, thereby transforming their operational workflows.
THE OCR PROCESS
- Image Acquisition: Before utilizing OCR, the desired content must first be captured and scanned to enter the process stream, producing an image or pdf file.
- Refining: If the content appears blurry after scanning, it may be hard for the software to recognize. Refining cleans and enhances the content within the documents to ensure the highest accuracy of recognition can be achieved.
- Text Recognition: OCR technology is then utilized to obtain the data. It firstly analyzes the documents, distinguishing the darker and lighter portions. Those dark portions are then scanned and processed to search for letters, numbers and other symbols. These are recognized by the system and outputted as text.
- Voting System Verification: To ensure the highest accuracy possible, documents are run through multiple different OCR software’s, the results of which then go through a voting system. If the majority agrees on the classification of a certain symbol, that is the symbol that will be outputted.
- Confirmation and storage: After being recognized and converted, the text is put through a spelling and grammar check to ensure successful recognition. After confirmation, it will be stored in a digital file where the content is editable and searchable.
THE ROLE OF AI
AI plays a vast role in ensuring OCR processes run as accurately and smoothly as possible. It is utilized to enhance the desired content by applying noise reduction as well as segmenting the text from the background. Additionally, it assists text recognition by applying modules trained on text datasets, as well as language processing to predict context. Furthermore, AI is employed to detect and correct any errors made by the OCR software. AI implementation in OCR is immensely beneficial as it is constantly learning and improving, becoming more robust over time.
BENEFITS
- Enhanced productivity and efficiency
- Enables automated data entry
- Improved accessibility through search capabilities
- Storage and labor cost reduction
- Streamlined workflows and enhanced document management
- Accurate and accessible record-keeping
- Reduces carbon footprint
- Capable of processing documents of any size
- Reduction of errors from manual input
- Utilizes AI to improve efficiency
ECM INTEGRATION
OCR is a crucial component of ECM solutions, significantly enhancing document management by converting paper documents into searchable digital formats, helping to decrease content chaos and disorganization. The automation of data entry and processing serves to streamline workflows and reduce manual errors, increasing overall efficiency and productivity. It also contributes to reducing costs associated with physical storage, as well as lowering labor costs. Overall, OCR plays a part in ECMs purpose of simplifying and improving business processes and reducing the use of paper.