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Image indexing using composite color and shape invariant features

机译:使用复合颜色和形状不变特征的图像索引

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New sets of color models are proposed for object recognition invariant to a change in view point, object geometry and illumination. Further, computational methods are presented to combine color and shape invariants to produce a high-dimensional invariant feature set for discriminatory object recognition. Experiments on a database of 500 images show that object recognition based on composite color and shape invariant features provides excellent recognition accuracy. Furthermore, object recognition based on color invariants provides very high recognition accuracy whereas object recognition based entirely on shape invariants yields very poor discriminative power. The image database and the performance of the recognition scheme can be experienced within PicToSeek: on-line as part of the ZOMAX system at: http://www.wins.uva.nl/research/isis/zomax/.
机译:提出了新的颜色模型集,用于不变的视点,物体的几何形状和照明变化的物体识别。此外,提出了将颜色和形状不变性相结合以产生用于区分对象识别的高维不变性特征集的计算方法。在包含500张图像的数据库上进行的实验表明,基于复合颜色和形状不变特征的物体识别可提供出色的识别精度。此外,基于颜色不变性的物体识别提供了很高的识别精度,而完全基于形状不变性的物体识别产生了很差的判别能力。图像数据库和识别方案的性能可以在PicToSeek:在线体验中,作为ZOMAX系统的一部分,位于:http://www.wins.uva.nl/research/isis/zomax/。

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