Detecting Korean Characters in Natural Scenes by Alphabet Detection and Agglomerative Character Construction

Abstract

This paper considers the Korean character detection problem. Unlike English where an alphabet constitutes a character, the Korean character is composed of more than two Korean alphabets, where they could be either connected or separated, relying on the Korean character font. Also, the Korean has two character structures which constitute a nested structure. These properties make the Korean character detection problem difficult. In this paper, we divide the Korean character detection problem into two subproblems, Korean alphabet detection and Korean character construction, and redefine the Korean character structures to efficiently detect Korean characters. Based on the new structures, we train four independent Korean alphabet detectors, and perform a sequential alphabet detection process with a specific detection order, to eliminate false alarms caused during detection procedure. Finally, the detected alphabets are grouped into the Korean characters by an agglomerative character construction algorithm. To evaluate our method, we carried out some experiments on a public dataset with several alternatives, and showed that our proposed Korean character detection method has outperformed other methods. © 2016 IEEE.