&lt;title&gt;Character segmentation algorithm for recognition of vehicle license plate&lt;/title&gt;

Tyan, JennKwei; Neubauer, C.; Goganovic, Ljubisa

doi:10.1117/12.369260

Cited by 2 publications

(4 citation statements)

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“…As a result, the corresponding character recognition is immediately available as well. Our previous work has demonstrated the feasibility of the character segmentation method [10].…”

Section: Recognition-based Character Segmentationmentioning

confidence: 99%

“…A component is suspicious having touching characters as its confidence measure is low and its dimension is large. We define a discrimination function based on contour projection RecognitionBased Character Segmentation that can be applied for identifying possible split points for such a component [10]. However, it is possible that a split point causes a component to be broken.…”

Section: Recognition-based Character Segmentationmentioning

confidence: 99%

“…A hybrid classifier combining neural network and template matching techniques performs character recognition [10,11]. In the neural network classifier, a three-layered perceptron is constructed and training is performed by error back-propagation.…”

Section: Hybrid Classifier-based Character Recognitionmentioning

confidence: 99%

See 2 more Smart Citations

<title>Automatic document reading system for technical drawings</title>

Tyan

Fang

2001

SPIE Proceedings

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The reading of technical drawings is a complex task for automatic document processing. In this paper we present a system for reading textual descriptions from technical drawings, which provides capabilities for converting paper-based documents into an electronic archiving database system. The proposed system consists of four major processing elements: form learning, form localization, optical character recognition (OCR), and result verification. The algorithms of each element are dedicated to solve the practical problems in reading technical drawing documents. Among them, form localization and OCR are the key processes for automation. Experimental results have shown the feasibility and efficiency of our approaches.

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“…As a result, the corresponding character recognition is immediately available as well. Our previous work has demonstrated the feasibility of the character segmentation method [10].…”

Section: Recognition-based Character Segmentationmentioning

confidence: 99%

Section: Recognition-based Character Segmentationmentioning

confidence: 99%

See 1 more Smart Citation

<title>Automatic document reading system for technical drawings</title>

Tyan

Fang

2001

SPIE Proceedings

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“…Similar approaches have been used for example in [91.The coarse localization relies basically on the fact, that a license plate, and in particular the text within the license plate. Details of the fine localization and segmentation algorithms are given in [11]. Vertical edges are computed and a saliency map is generated as shown in Figure 2.…”

Section: Localization Of License Platesmentioning

confidence: 99%

<title>License plate recognition with an intelligent camera</title>

1999

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This paper describes a robust car identification system for surveillance of parking lot entrances that runs completely on a stand alone low cost intelligent camera. In order to meet accuracy and speed requirements hierarchical classifiers and coarse to fine search techniques are applied at each recognition stage from localization, segmentation to classification. The paper gives an overview of the applied image processing techniques and focuses in particular on the character classification part. Character recognition is based on a convolutional neural network that proved to generalize better than a fully connected multi-layer perceptron.

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<title>Character segmentation algorithm for recognition of vehicle license plate</title>

Cited by 2 publications

References 0 publications

<title>Automatic document reading system for technical drawings</title>

<title>Automatic document reading system for technical drawings</title>

<title>License plate recognition with an intelligent camera</title>

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