Often, the examination of objects where condition is important do not use technology to its full capacity. Currently, these examinations are done by hand and by eye. Though traditional, this process is more costly, inconsistent, and generally not reproducible. To solve this problem, our team has investigated and prototyped an algorithmically driven processing system wherein specific criteria are examined using computer vision and machine learning resulting in precise, consistent and reproducible conclusions.