A low cost compact diagnostic has many implications in today’s society. Smart phone technology has exponentially grown and with it the imaging capabilities associated with smart phones. The goals of this research are i) to determine the feasibility of combining in the field smart phone images with color dependent assay results, ii) to develop a MatLab® image analysis code to analyze these results, and iii) compare limits of detection between the un-aided eye and MatLab® image analysis software. Orange G dye is used to create a stock solution and subsequent titers for analysis. Autocad is used to design an assay platform of 10x10 wells that are printed via a Xerox® Phaser printer with wax ink onto nitrocellulose paper. Dilutions are performed and pipetted into the wells. The image analysis code is used to determine hue, saturation, and value (HSV) values of wells. A limit of detection study using the dye is performed. HSV values are used to form calibration curves. The resulting curve fit equations are then integrated into the image analysis code to determine dye concentration. Finally, the complete capability is demonstrated by using an analogous 10x10 well experimental nitrocellulose sheet, which included a follow-up experiment via a spot check analysis. This study illustrates the feasibility of a low cost image analysis as a tool for lateral flow assay diagnostic versus the unaided eye. Future work includes using this protocol in conjunction with a lateral flow immunoassay and developing an application for the analysis.