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首页> 外文会议>Conference on Image Processing: Algorithms and Systems III; 20040119-20040121; San Jose,CA; US >An affine point-set and line invariant algorithm for photo-identification of gray whales
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An affine point-set and line invariant algorithm for photo-identification of gray whales

机译：仿射点集和线不变算法用于灰鲸的光识别

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摘要

This paper presents an affine point-set and line invariant algorithm within a statistical framework, and its application to photo-identification of gray whales (Eschrichtius robustus). White patches (blotches) appearing on a gray whale's left and right flukes (the flattened broad paddle-like tail) constitute unique identifying features and have been used here for individual identification. The fluke area is extracted from a fluke image via the live-wire edge detection algorithm, followed by optimal thresholding of the fluke area to obtain the blotches. Affine point-set and line invariants of the blotch points are extracted based on three reference points, namely the left and right tips and the middle notch-like point on the fluke. A set of statistics is derived from the invariant values and used as the feature vector representing a database image. The database images are then ranked depending on the degree of similarity between a query and database feature vectors. The results show that the use of this algorithm leads to a reduction in the amount of manual search that is normally done by marine biologists.
机译：本文提出了一个统计框架内的仿射点集和线不变算法，并将其应用于灰鲸（Eschrichtiusrobustus）的光识别。出现在灰鲸左右鳞片（扁平的宽桨状尾巴）上的白色斑块（斑点）构成独特的识别特征，并已在此处用于个人识别。通过实线边缘检测算法从from虫图像中提取fl虫区域，然后对fl虫区域进行最佳阈值处理以获得斑点。斑点的仿射点集和线不变性是基于三个参考点提取的，即左，右尖端和fl骨上的中间凹口状点。从不变值中得出一组统计信息，并将其用作代表数据库图像的特征向量。然后根据查询和数据库特征向量之间的相似度对数据库图像进行排名。结果表明，该算法的使用导致海洋生物学家通常完成的手动搜索量减少。

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