• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.41-51
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• 2002

Recently, many studies extracting the geography information using digital aerial image have been implemented. But it is very difficult that automatically recognizing objects using edge detection method on the aerial image, and so that work have practiced manually or semi-automatically. Therefore, in this study, we have removed impedimental elements for recognition using the image which overlapped the significant information bands of brightness-sliced aerial images, then have developed the algorithm which can automatically recognize and extract road information and we will try to apply that method when we develope a system. For this, first of all, we have developed the 'template conformal-transformation moving operator' for automatically recognizing crosswalk area from crosswalk band image and the 'window normal search algorithm' which is able to track road area based on long-side length of crosswalk, so that we have proposed the method that can extract directly the road information from the aerial image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.586-599
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• 2012

This paper proposes a fast face detection and tracking method which uses depth images as well as RGB images. It consists of the face detection procedure and the face tracking procedure. The face detection method basically uses an existing method, Adaboost, but it reduces the size of the search area by using the depth image. The proposed face tracking method uses a template matching technique and incorporates an early-termination scheme to reduce the execution time further. The results from implementing and experimenting the proposed methods showed that the proposed face detection method takes only about 39% of the execution time of the existing method. The proposed tracking method takes only 2.48ms per frame with $640{\times}480$ resolution. For the exactness, the proposed detection method showed a little lower in detection ratio but in the error ratio, which is for the cases when a detected one as a face is not really a face, the proposed method showed only about 38% of that of the previous method. The proposed face tracking method turned out to have a trade-off relationship between the execution time and the exactness. In all the cases except a special one, the tracking error ratio is as low as about 1%. Therefore, we expect the proposed face detection and tracking methods can be used individually or in combined for many applications that need fast execution and exact detection or tracking.

• Journal of Plant Biotechnology
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• v.36 no.4
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• pp.384-391
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• 2009

Previously, two events (H15 and B20) of transgenic pepper (Capsicum annuum L.) that enhanced resistance to Cucumber mosaic virus (CMV) by the introduction of CMV coat protein (CP) gene were constructed. Presently, a single copy number of the CP gene was revealed in H15 and B20 by Southern blot. To predict possible unintended effects due to transgene insertion in an endogenous gene, we carried out sequencing of the 5'-flanking region of the CP gene and a Blastbased search. The results revealed that insertion of the transgene into genes encoding putative proteins may occur in the H15 and B20 transgenic event. Mutiplex polymerase chain reaction (PCR) for simultaneous detection and identification of transgenic pepper was conducted with a set of nine primers. Both transgenic event were differentiated from non-transgenic event by the presence of 267 bp and 430 bp PCR products indicative of CP gene specific primer pairs and primer pairs targeting the CP gene and 35S promoter. H15 and B20 uniquely possessed a 390 bp and 596 bp PCR product, respectively. The presence of a 1115 bp product corresponding to intrinsic pepper actin gene confirmed the use of pepper DNA as the PCR template. The primer set and PCR conditions used presently may allow the accurate and simple identification of CMV resistant transgenic pepper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1825-1838
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• 2012

This paper proposes a fast face detection and tracking method which uses depth images as well as RGB images. It consists of the face detection procedure and the face tracking procedure. The face detection method basically uses an existing method, Adaboost, but it reduces the size of the search area by using the depth information and skin color. The proposed face tracking method uses a template matching technique and incorporates an early-termination scheme to reduce the execution time further. The results from implementing and experimenting the proposed methods showed that the proposed face detection method takes only about 39% of the execution time of the existing method. The proposed tracking method takes only 2.48ms per frame. For the exactness, the proposed detection method and previous method showed a same detection ratio but in the error ratio, which is about 0.66%, the proposed method showed considerably improved performance. In all the cases except a special one, the tracking error ratio is as low as about 1%. Therefore, we expect the proposed face detection and tracking methods can be used individually or in combined for many applications that need fast execution and exact detection or tracking.