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Showing papers on "Sketch recognition published in 1991"


Proceedings ArticleDOI
08 Jul 1991
TL;DR: Preliminary experiments with computer simulation show that this approach is promising for both of the applications of the proposed model of selective attention, which has a function of segmenting patterns, as well as the function of recognizing patterns.
Abstract: Selective attention is one of the most essential mechanisms for visual pattern recognition. One of the authors had previously proposed a model of selective attention, which has a function of segmenting patterns, as well as the function of recognizing patterns. The idea of this selective attention model can be extended to be used for several applications. The structure of the model used for connected character recognition is discussed. The authors offer two examples of its applications. One is the recognition and segmentation of connected characters in cursive handwriting of English words. Another example is the recognition of Chinese characters. Preliminary experiments with computer simulation, in which only a small number of characters have been taught to the models, show that this approach is promising for both of the applications. >

32 citations


Proceedings ArticleDOI
09 Apr 1991
TL;DR: An approach to generalize the hypothesis and test recognition paradigm for multisensory environments and fairly generic object models based on a generic representation of feature accuracy performs fusion both at the numeric (geometric) and at the symbolic (recognition) levels.
Abstract: The authors propose an approach to generalize the hypothesis and test recognition paradigm for multisensory environments and fairly generic object models. Matching, prediction and localization procedures are based on a generic representation of feature accuracy. This generic approach performs fusion both at the numeric (geometric) and at the symbolic (recognition) levels. Its reliability is illustrated by several real-world examples demonstrating recognition of real objects in complex cluttered environments using four types of sensory data: contour images (two viewpoints), stereovision 3-D line segments, range 3-D faces, and color images. >

15 citations



Proceedings ArticleDOI
25 Feb 1991
TL;DR: An image character recognition project is described whose purpose is to investigate the applicability of artificial neural system (ANS) technology to the automated reading of account number fields from copies of credit card charge receipts.
Abstract: An image character recognition project is described whose purpose is to investigate the applicability of artificial neural system (ANS) technology to the automated reading of account number fields from copies of credit card charge receipts. The advantage of the ANS approach for such pattern recognition tasks is that it is both nonlinear and adaptive. After training with a large number of other noisy patterns, the neural network recognition system can correctly identify all of the numbers in the figure without having seen these particular images before. Although the emphasis of this proof-of-concept study is on reducing credit industry costs by improving the accuracy of recognition, this approach promises to ultimately offer a significant boost in processing speed as well. The account number processing problem, the system developed for its solution, and the analysis of its performance are described. >

4 citations


Proceedings ArticleDOI
28 Aug 1991

2 citations


Proceedings ArticleDOI
TL;DR: The simplification of the classical object recognition methodology is illustrated by the network based algorithm development of a simple 2-D character recognition system and the term heterogenous input neuration is introduced.
Abstract: The utilization of artificial neural networks (ANN) in the area of signal and image processing applications is showing great promise. The simplification of the classical object recognition methodology is illustrated by the network based algorithm development of a simple 2-D character recognition system. The hardware implementation of such a system is also discussed. An example of a network-based solution to a target recognition problem utilizing single sensor acoustic data is also addressed. The term heterogenous input neuration is introduced.