Abstract
We address the problem of localizing objects using color, texture and shape. Given a handrawn sketch for querying an object shape, and its color and texture, the algorithm automatically searches the database images for objects which meet the query attributes. The database images do not need to be presegmented or annotated. The proposed algorithm operates in two stages. In the first stage, we use local texture and color features to find a small number of candidate images, and identify regions in the candidate images which share similar texture and color as the query example. To speed up the processing, the texture and color features are directly extracted from the Discrete Cosine Transform (DCT) compressed domain. In the second stage, we use a deformable template matching method to match the query shape to the image edges at the locations which possess the desired texture and color attributes. This algorithm is different from the other content-based image retrieval algorithms in that: (i) no presegmentation of the database images is needed, and (ii) the color and texture features are directly extracted from the compressed images. Experimental results show that substantial computational savings can be achieved utilizing multiple image cues.
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S.F. Chang and D.G. Messerschmitt. A new approach to decoding and compositing motion compensated DCT-based images. In Proc IEEE Int. Conf. Acoust. Speech Signal Proc., pages 421–424, 1993, Minneapolis, MN.
T. Chang and C.J. Kuo. Texture analysis and classification with tree-structured wavelet transform. IEEE Trans. Image Processing, 2(4):429–441, October 1994.
D. L. Gall. MPEG: a video compression standard for multimedia applications. Communications of the ACM, 34(4):47–58, 1991.
M. M. Gorkani and R. W. Picard. Texture orientation for sorting photos “at a glance”. Proc. of the 12th Int. Conf. on Pattern Recognition, Jerusalem, Israel, 67(5):A459–A464, October 1994.
U. Grenander and M. I. Miller. Representation of knowledge in complex systems. J. of Royal Statistical Society (B), 56(3):1–33, 1994.
A. K. Jain and F. Farrokhnia. Unsupervised Texture Segmentation Using Gabor Filters. Pattern Recognition, 24(12):1167–1186, 1991.
A.K. Jain, Y. Zhong, and S. Lakshmanan. Object matching using deformable templates. IEEE Trans. Pattern Anal. and Machine Intell., 18(3):267–278, March 1996.
M.E. Jernigan and F. D'Astous. Entropy-based texture analysis in the spatial frequency domain. IEEE Trans. Pattern Anal. and Machine Intell., 6(2), March 1984.
K. Karu, A. K. Jain, and R. M. Bolle. Is there any texture in the image? Pattern Recognition, 29(9):1437–1446, 1996.
M. Kass, A. Witkin, and D. Terzopoulos. Snakes: Active contour models. Int. J. Comput. Vision, 1(4):321–331, 1988.
W. Niblack, R. Barber, and W. Equitz. The QBIC project: Querying images by content using color, texture, and shape. Proc. SPIE Conf. on Storage and Retrieval for Image and Video Databases, 1908:173–187, 1993.
A. Pentland, R. W. Picard, and S. Sclaroff. Photobook: tools for content-based manipulation of image databases. Proc. SPIE Conf. on Storage and Retrieval for Image and Video Databases II, 2185-05, February 1994.
B. Shen and I.K. Sethi. Direct feature extraction from compressed images. In Proc. SPIE Conf. on Storage and Retrieval for Image and Video Databases IV, volume 2670, 1995.
M.J. Swain and D.H. Ballard. Color indexing. Int. J. Comput. Vision, 7(1):11–32, 1991.
A. Vailaya, Y. Zhong, and A. K. Jain. A hierarchical system for efficient image retrieval. In Proc. 13th Int. Conf. on Patter Recognition (ICPR), pages 356–360, Vienna. Austria, 1996.
B.C. Vemuri and A. Radisavljevic. From global to local, a continuum of shape models with fractal priors. Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages 307–313–627, New York City, NY, June 1993.
V.V. Vinod and H. Murase. Object location using complementary color features: histogram and DCT. In Proc. 13th Int. Conf. on Patter Recognition (ICPR), pages 554–559, Vienna, Austria, 1996.
G.K. Wallace. The JPEG still picture compression standard. Communications of the ACM, 34(4):31–44, 1991.
A. L. Yuille, P. W. Hallinan, and D. S. Cohen. Feature extraction from faces using deformable templates. Int. J. Comput. Vision, 8(2):133–144, 1992.
H. J. Zhang, C. Y. Low, and S. W. Smoliar. Video parsing and browsing using compressed data. Multimedia Tools and Applications, pages 89–111, 1995.
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© 1997 Springer-Verlag Berlin Heidelberg
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Zhong, Y., Jain, A.K. (1997). Object localization using color, texture and shape. In: Pelillo, M., Hancock, E.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 1997. Lecture Notes in Computer Science, vol 1223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62909-2_86
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DOI: https://doi.org/10.1007/3-540-62909-2_86
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