Invention Grant
US08369611B2 Compact handwriting recognition 有权
紧凑的手写识别

Compact handwriting recognition
Abstract:
One or more techniques and/or systems are disclosed for constructing a compact handwriting character classifier. A precision constrained Gaussian model (PCGM) based handwriting classifier is trained by estimating parameters for the PCGM under minimum classification error (MCE) criterion, such as by using a computer-based processor. The estimated parameters of the trained PCGM classifier are compressed using split vector quantization (VQ) (e.g., and in some embodiments, scalar quantization) to compact the handwriting recognizer in computer-based memory.
Public/Granted literature
Information query
Patent Agency Ranking
0/0