Text embedded in an image contains useful information for applications in the medical, industrial, commercial, and research fields.\r\nWhile many systems have been designed to correctly identify text in images, no work addressing the recognition of degraded text\r\non clear plastic has been found. This paper posits novel methods and an apparatus for extracting text from an image with the\r\npractical assumption: (a) poor background contrast, (b) white, curved, and/or differing fonts or character width between sets of\r\nimages, (c) dotted text printed on curved reflective material, and/or (d) touching characters.Methods were evaluated using a total\r\nof 100 unique test images containing a variety of texts captured from water bottles. These tests averaged a processing time of ~10\r\nseconds (using MATLAB R2008A on an HP 8510W with 4G of RAM and 2.3 GHz of processor speed), and experimental results\r\nyielded an average recognition rate of 90 to 93% using customized systems generated by the proposed development.
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