PRODUCT & TECH
The adoption of optical character recognition in mining
Optical Character Recognition
( OCR ) is process of classification of optical patterns contained in a digital image . The character recognition is achieved through segmentation , feature extraction and classification . This chapter presents the basic ideas of OCR needed for a better understanding of the book . The chapter starts with a brief background and history of OCR systems . Then the different techniques of OCR systems such as optical scanning , location segmentation , pre-processing , segmentation , representation , feature extraction , training and recognition and post-processing .
The different applications of OCR systems are highlighted next followed by the current status of the OCR systems . The process of using OCR on a mine or business involves creating check sheets using management data and relevant exploratory questions . These sheets can range from information pertaining to safety , production or just general employee feedback questions .
Information is captured on physical sheets and collected at a central point for digital scanning . The system reads , populates and actions data in less than 30 seconds per sheet , so that all data is available digitally . By linking predefined answers to certain questions defined in the risk model , called mapped questions , the system can automatically trigger predefined actions by utilizing the action manager . Mobile device capability allows data to be captured immediately and on-site , while data is fresh and visually available . The use of OCR systems eliminates the need for data to be read and captured by humans , negating the possibility of human error . This system will benefit any business that wishes to streamline operational safety , improve efficiency and eliminate the factor of human error in data gathering .
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