ISIS Group, Faculty of WINS, Amsterdam, The Netherlands.
IEEE Trans Image Process. 2000;9(1):102-19. doi: 10.1109/83.817602.
We aim at combining color and shape invariants for indexing and retrieving images. To this end, color models are proposed independent of the object geometry, object pose, and illumination. From these color models, color invariant edges are derived from which shape invariant features are computed. Computational methods are described to combine the color and shape invariants into a unified high-dimensional invariant feature set for discriminatory object retrieval. Experiments have been conducted on a database consisting of 500 images taken from multicolored man-made objects in real world scenes. From the theoretical and experimental results it is concluded that object retrieval based on composite color and shape invariant features provides excellent retrieval accuracy. Object retrieval based on color invariants provides very high retrieval accuracy whereas object retrieval based entirely on shape invariants yields poor discriminative power. Furthermore, the image retrieval scheme is highly robust to partial occlusion, object clutter and a change in the object's pose. Finally, the image retrieval scheme is integrated into the PicToSeek system on-line at http://www.wins.uva.nl/research/isis/PicToSeek/ for searching images on the World Wide Web.
我们的目标是结合颜色和形状不变量进行图像索引和检索。为此，提出了与物体几何形状、物体姿态和光照无关的颜色模型。从这些颜色模型中，得出了颜色不变量边缘，从中计算出形状不变量特征。描述了将颜色和形状不变量组合成一个统一的高维不变量特征集，以进行有区别的目标检索的计算方法。实验是在一个由 500 幅取自真实场景中多色人造物体的图像组成的数据库上进行的。从理论和实验结果可以得出结论，基于组合颜色和形状不变量特征的目标检索提供了非常高的检索精度。基于颜色不变量的目标检索提供了非常高的检索精度，而完全基于形状不变量的目标检索则具有较差的区分能力。此外，该图像检索方案对部分遮挡、物体杂乱和物体姿态变化具有高度的鲁棒性。最后，图像检索方案集成到在线的 PicToSeek 系统中，网址为 http://www.wins.uva.nl/research/isis/PicToSeek/，用于在万维网上搜索图像。
