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At least 325 records · Page 18Linked to original sources
PubMed2004

Discriminative learning quadratic discriminant function for handwriting recognition.

In character string recognition integrating segmentation and classification, high classification accuracy and resistance to noncharacters are desired to the underlying classifier. In a previous evaluation study, the modified quadratic discriminant function (MQDF) proposed by Kimura et al. was shown to be superior in noncharacter resistance but inferior in classification accuracy to neural networks. This paper proposes a discriminative learning algorithm to optimize the parameters of MQDF with aim to improve the classification accuracy while preserving the superior noncharacter resistance. We refer to the resulting classifier as discriminative learning QDF (DLQDF). The parameters of DLQDF adhere to the structure of MQDF under the Gaussian density assumption and are optimized under the minimum classification error (MCE) criterion. The promise of DLQDF is justified in handwritten digit recognition and numeral string recognition, where the performance of DLQDF is comparable to or superior to that of neural classifiers. The results are also competitive to the best ones reported in the literature.

Discrimination Learning↗
PubMed2006

Minimum classification error training for online handwriting recognition.

This paper describes an application of the Minimum Classification Error (MCE) criterion to the problem of recognizing online unconstrained-style characters and words. We describe an HMM-based, character and word-level MCE training aimed at minimizing the character or word error rate while enabling flexibility in writing style through the use of multiple allographs per character. Experiments on a writer-independent character recognition task covering alpha-numerical characters and keyboard symbols show that the MCE criterion achieves more than 30 percent character error rate reduction compared to the baseline Maximum Likelihood-based system. Word recognition results, on vocabularies of 5k to 10k, show that MCE training achieves around 17 percent word error rate reduction when compared to the baseline Maximum Likelihood system.

Algorithms↗
PubMed1979

Differences in neural organization between individuals with inverted and noninverted handwriting postures.

Levy's hypothesis that movements of the distal musculature are controlled by ipsilateral motor projections in subjects with inverted writing posture was tested in a reaction-time experiment with lateralized auditory, tactual, and visual stimulation. Subjects were required to depress a response key with the left or right index finger when they detected a stimulus in either the left or right sensory field. Writers with noninverted posture responded quickest to stimuli on the same side as the responding hand in all modalities tested, whereas inverted writers showed this pattern only in auditory and tactual modalities. In the visual modality, they responded quickest to stimuli on the side opposite the responding hand. Because Levy's hypothesis predicts the latter effect in all modalities for inverted writers, it is challenged by our results, which suggest that inverted writers may be characterized by anomalous visual or visuomotor organization.

Behavior↗