Character recognition is vital in digitizing physical media, such as books or research papers, into electronic formats. To transcribe these texts manually can be a long, tedious process. The purpose of this project is to create a semi-robust character identification module to recognize and digitize analog images. This will be accomplished by using digital signal processing (DSP) techniques such as the Fourier transform and filters in conjunction with statistics to identify English alphabet characters. In addition, we will explore the ability to identify handwritten characters and conjoin them into more meaningful words and sentences.