디더링과 모듈 구조의 다중 MLP를 이용한 무제약 필기체 숫자 인식

Unconstrained Numeral Recognition Using Dithering and Multiple Modular MLPs

In this paper, we propose a method of unconstrained handwritten numeral recognition using image dithering and multiple modular MLPs. The set of sample numeral patterns is subdivided into clusters which are extended by their radius. On each extended cluster, we constructed MLPs network as the expert recognizer of corresponding cluster. The gating network is also trained by an MLPs to weigh the outputs of expert MLPs. In training and test phase of the recognizer, we utilize the multiple dithered numeral images and the combination of the outputs for corresponding dithered images. Experimental results show that our recognition method works very well.