Recognizing Thai handwritten characters and words for human–computer interaction

Normally, people use a keyboard to interact with a computer. This type of interaction has two main problems; typing speed and typing error. This paper proposes a non-keyboard computer interaction by using a write-pen or mouse to write Thai handwritten characters and words, using a feature-based, fuzzy logic and object-oriented approach (FBFLOOA) to recognize on-line handwritten Thai characters and words. The feature-based concept is used to extract handwritten character features, the fuzzy logic set is used to identify uncertain handwritten character shapes and the object-oriented approach is used to analyse, design and implement a handwritten character and word recognition program. Two phases of Thai handwritten character and word recognition are proposed. The first phase uses only the FBFLOOA to recognize a handwritten character and the second phase uses FBFLOOA combined with a Thai dictionary file to seek a correct answer for a rejected recognition character. The first phase experimental results show a recognition accuracy of 89.24%, 9.20% misrecognition and 1.56% rejection. The second phase precision results are 97.82%, 0.62% misrecognition and 1.56% rejection. Both phases have an average recognition speed of 6.72s per character. The FBFLOOA-executed program size is 189 KB and the Thai dictionary file is 853 KB, which makes FBFLOOA available for notebooks, mobile phones, calculators and pocket computers.