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TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)
TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)
Current Result Document :
4
/ 4
ÀÌÀü°Ç
ÇѱÛÁ¦¸ñ(Korean Title)
Image Retrieval Method Based on IPDSH and SRIP
¿µ¹®Á¦¸ñ(English Title)
Image Retrieval Method Based on IPDSH and SRIP
ÀúÀÚ(Author)
Xu Zhang
Baolong Guo
Yunyi Yan
Wei Sun
Meng Yi
¿ø¹®¼ö·Ïó(Citation)
VOL 08 NO. 05 PP. 1676 ~ 1689 (2014. 05)
Çѱ۳»¿ë
(Korean Abstract)
¿µ¹®³»¿ë
(English Abstract)
At present, the Content-Based Image Retrieval (CBIR) system has become a hot research topic in the computer vision field. In the CBIR system, the accurate extractions of low-level features can reduce the gaps between high-level semantics and improve retrieval precision. This paper puts forward a new retrieval method aiming at the problems of high computational complexities and low precision of global feature extraction algorithms. The establishment of the new retrieval method is on the basis of the SIFT and Harris (APISH) algorithm, and the salient region of interest points (SRIP) algorithm to satisfy users'''' interests in the specific targets of images. In the first place, by using the IPDSH and SRIP algorithms, we tested stable interest points and found salient regions. The interest points in the salient region were named as salient interest points. Secondary, we extracted the pseudo-Zernike moments of the salient interest points¡¯ neighborhood as the feature vectors. Finally, we calculated the similarities between query and database images. Finally, We conducted this experiment based on the Caltech-101 database. By studying the experiment, the results have shown that this new retrieval method can decrease the interference of unstable interest points in the regions of non-interests and improve the ratios of accuracy and recall.
Å°¿öµå(Keyword)
Image Processing
Image Retrieval
Interest Points
Salient Region
local distribution features
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