Writer-adaptation for on-line handwritten character recognition
نویسندگان
چکیده
We have designed a writer-adaptive character recognition system for on-line characters entered on a touch-terminal. It is based on a Time Delay Neural Network (TDNN) that is rst trained on examples from many writers to recognize digits and uppercase letters. The TDNN without its last layer serves as a preprocessor to an Optimal Hyperplane classi er, that can be easily retrained to peculiar writing styles. This combination allows for fast writer dependent learning of new letters and symbols. The adaptation module is memory and speed e cient.
منابع مشابه
Allograph Based Writer Adaptation for Handwritten Character Recognition
Writer adaptation is the process of converting a generic (writer-independent) handwriting recognizer into a personalized (writer-dependent) recognizer with improved accuracy for a particular user. While training the generic recognizer uses large amounts of data from several writers, the adaptation process uses only a few samples from a single user. In this paper we present a) an automatic appro...
متن کاملHandwritten text recognition through writer adaptation
Handwritten text recognition is a problem rarely studied out of specific applications for which lexical knowledge can constrain the vocabulary to a limited one. In the case of handwritten text recognition, additional information can be exploited to characterize the specificity of the writing. This knowledge can help the recognition system to find coherent solutions from both the lexical and the...
متن کاملOn-line Handwritten Devanagari Character Recognition using Fuzzy Directional Features
This paper describes a new feature set for use in the recognition of on-line handwritten Devanagari script based on Fuzzy Directional Features. Experiments are conducted for the automatic recognition of isolated handwritten character primitives (sub-character units). Initially we describe the proposed feature set, called the Fuzzy Directional Features (FDF) and then show how these features can ...
متن کاملUnsupervised writer adaptation applied to handwritten text recognition
This paper deals with the problem of o3-line handwritten text recognition. It presents a system of text recognition that exploits an original principle of adaptation to the handwriting to be recognized. The adaptation principle is based on the automatic learning, during the recognition, of the graphical characteristics of the handwriting. This on-line adaptation of the recognition system relies...
متن کاملAdaptive Context Processing in On-line Handwritten Character Recognition
We propose a new approach to context processing in on-line handwritten character recognition (OLCR). Based on the observation that writers often repeat the strings that they input, we take the approach of adaptive context processing (ACP). In ACP, the strings input by a writer are automatically added to a dictionary designated for ACP. This dictionary thereby can provide good coverage of the st...
متن کامل