As more vehicles and devices are becoming equipped with cameras, computer vision technologies can significantly enhance functionalities. Among various computer vision applications, alphabet recognition has been an important application. Alphabet recognition is a basic operation in text recognition of natural images, which can be used to obtain useful information from visual information. It can be used for vehicles or autonomous moving machines such as drones or robots to understand surrounding environments. A main difficulty is that alphabets can take various sizes and orientations. Thus, it is desirable to develop recognition algorithms that are size and rotation invariant. In this paper, we propose alphabet recognition algorithms based on the recently proposed angle-distance map, which is robust against size and rotation variations. Using the two features (distance and angle), the angle-distance map is generated, and a rotation invariant matching algorithm is developed. Since the distance is normalized, the map is size-invariant. Experimental results showed promising results.