{"id":2137,"date":"2023-03-10T19:49:53","date_gmt":"2023-03-10T10:49:53","guid":{"rendered":"https:\/\/bestpathresearch.com\/www\/?p=2137"},"modified":"2023-06-02T19:55:03","modified_gmt":"2023-06-02T10:55:03","slug":"202303101234","status":"publish","type":"post","link":"https:\/\/bestpathresearch.com\/en\/2023\/03\/10\/202303101234\/","title":{"rendered":"Publication of the paper \u201cAutomatic Detection and Rectification of Paper Receipts on Smartphones\u201d"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\t\t\t\t\nBest Path Research has published the results of its latest research on detecting and rectifying paper receipts using a smartphone camera on the arXiv paper repository at:\n

<\/p>\nhttps:\/\/arxiv.org\/abs\/2303.05763<\/a>\n

<\/p>\nIn this research we developed a novel technique to perform corner detection on potentially deformed objects so as to detect each of the four corners of a paper receipt while ignoring spurious, interfering objects (that might also have corners).\nHaving identified the four unique corners of the receipt, we use a traditional computer vision technique, called a perspective transform, to convert the potentially deformed image into a straight or rectangular image (as if viewed directly overhead, i.e. the so-called \u201cbird\u2019s eye view\u201d).\n

<\/p>\nHaving straightened the image in this fashion, the expectation is that all lines in the rectified image are now horizontally aligned, thus making it much easier to perform downstream processing tasks, such as optical character recognition (OCR), or named-entity (NE) detection, on the rectified image.\n<\/span>\n\n\n\n