발간년도 : [2016]
| 논문정보 |
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| 논문명(한글) |
[Vol.11, No.1] A Efficient Salient Point Extracting Technique by Using Multiple Wavelet Transform |
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| 논문투고자 |
Nam-Oh Kang, Sa-Joon Park, Jae-Ho Kim |
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| 논문내용 |
The extraction of robust feature points from images is one of the fundamental operations required in image processing. Among the kinds of salient point, as corner in image contains local features, it is used to achieve image recognition, image registration, and object tracking etc. Hence, extracting corners accurately is significant to image processing as well as constructing an efficient and effective image processing system. Harris corner detection algorithm, among many corner detection algorithms, is well known for extracting robust corners. It is used to improve feature description algorithms such as Scale-invariant feature transform(SIFT) and Speeded Up Robust Feature(SURF). It is also employed in the development of various image processing applications such as object segmentation, object tracking, image recognition, and image registration etc. Therefore, a lot of research has been conducted to improve the Harris corner detection algorithm. In this paper, we proposed a technique which can extract salient points efficiently by analysing wavelet subbands of wavelet-tansformed image. Experiments were performed using Lena image and they showed that the proposed technique produces more rapidly than Harris corner detection algorithm does. |
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