This document describes research on developing an Android application to identify apple diseases using image processing techniques. An algorithm was created using OpenCV and Java that takes a picture of an apple, applies grayscale conversion for pre-processing, and uses template matching to identify if the apple has bitter rot, blister spot, or scab. The algorithm had success identifying diseases correctly in 71% of cases, though some diseases were only 33% accurate. Future work to improve accuracy could explore alternative methods like cascade classification and verifying the object is an apple first before detecting diseases. The goal is to create a cost-effective mobile tool for farmers to self-identify diseases without expert help.