基于轮廓边缘检测和SIFT算法的叶片识别

Shubham Lavania, Palash Sushil Matey
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引用次数: 26

摘要

本文介绍了计算机视觉领域中比较研究的两种先进方法。第一种方法是实现基于关键描述符值的标量不变傅立叶变换(SIFT)算法。第二种方法是利用均值投影算法进行基于轮廓的角点检测和分类。与其他曲率尺度空间(CSS)系统相比,该系统的优点是与最近的标准角点检测技术相比,有更少的假阳性(FP)和假阴性(FN)点。在flavia数据库上对两种算法进行了性能分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leaf recognition using contour based edge detection and SIFT algorithm
The paper presents two advanced methods for comparative study in the field of computer vision. The first method involves the implementation of the Scalar Invariant Fourier Transform (SIFT) algorithm for the leaf recognition based on the key descriptors value. The second method involves the contour-based corner detection and classification which is done with the help of Mean Projection algorithm. The advantage of this system over the other Curvature Scale Space (CSS) systems is that there are fewer false-positive (FP) and false-negative (FN) points compared with recent standard corner detection techniques. The performance analysis of both the algorithm was done on the flavia database.
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