• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1713-1723
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• 1999

Optical character recognition(OCR) might be the most plausible method in building database out of printed matters. This paper describes the points to be considered when one selects an OCR system in order to build database. Based on the considerations, we evaluated four commercial OCR systems, and chose one which shows the best recognition rate to build OCT-text database. The subject text, the KT-test collection, is a set of abstracts from proceedings of different printing quality, fonts, and formats. KT-test collection is also provided with typed text database. Recognition rate was calculated by comparing the recognition result with the typed text. No preprocessing such as learning and slant correction was applied to the recognition process in order to simulate a practical environment. The result shows 90.5% of character recognition rate over 970 abstracts. This recognition rate is still insufficient for practical use. The errors in OCR texts are different from those of manually typed texts. In this paper, we classify the errors in OCR texts for the further research.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.45-56
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• 2001

To acquire seabed information, the mosaic images of the seabed were generated using Side Scan Sonar. Short time energy function which is needed for slant range correction is proposed to get the height of Tow-Fish to the reflected acoustic amplitudes of each ping, and that leads to a mosaic image without water column. While generating mosaic image, maximum value, last value and average value are used for the measure of a pixel in the mosaic image and 3-D information was kept by using acoustic amplitudes which were heading for specific direction. As a generating method of mosaic image, low resolution mosaic image which is over 1m/pixel resolution was generated for whole survey area first, and then high resolution mosaic image which is generated under 0.1m/pixel resolution was generated for the selected area. Rocks, ripple mark, sand wave, tidal flat and artificial fish reef are found in the mosaic image.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.423-431
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• 2016

In general LPR(License Plate Recognition) in outdoor image is not so simple differently from in the image captured from manmade environment, because of geometric shape distortion and large illumination changes. this paper proposes three techniques for LPR in outdoor images captured from CCTV. At first, a serially connected multi-stage Adaboost LP detector is proposed, in which different complementary features are used. In the proposed detector the performance is increased by the Haar-like Adaboost LP detector consecutively connected to the MB-LBP based one in serial manner. In addition the technique is proposed that makes image processing easy by the prior determination of LP type, after correction of geometric distortion of LP image. The technique is more efficient than the processing the whole LP image without knowledge of LP type in that we can take the appropriate color to gray conversion, accurate location for separation of text/numeric character sub-images, and proper parameter selection for image processing. In the proposed technique we use DBN(Deep Belief Network) to achieve a robust character recognition against stroke loss and geometric distortion like slant due to the incomplete image processing.