快速SUSAN-Laplace角点算法

提出了一种新的SUSAN-Laplace角点算子。新算子首先使用拉普拉斯-高斯核对图像进行卷积,并将图像转换为二值或三值图像,然后使用SUSAN算子检测角点。这样既快速又具有SUSAN算子的位置精确性。SUSAN- Laplace角子具有较好的旋转、仿射、光照、尺度和噪声不变性,其计算速度也较快,比Harris角点快1.5倍,比SUSAN角点快6倍。应用中SUSAN-Laplace角子有一种快速算法,快速算法在计算拉普拉斯-高斯卷积时使用移位运算代替全部乘除法运算,能进一步提高计算速度。SUSAN-Laplace角子较其它角点算法能产生更丰富的角点,应用到SIFT算法中可提高对小目标的识别能力。

A fast Laplace-SUSAN corner detector

A novel Laplace-SUSAN corner detector is described.The original image Convolved by a Laplacian of Gaussian filter is translated to a binary or ternary image according to threshold,in which the algorithm uses the SUSAN detector to detect corners.The Laplace-SUSAN detector has excellent high-speed and location accuracy,that can perform 1.5 times faster than Harris and 6 times faster than SUSAN and whose corner is shown to be invariant to image rotation and scale and robust across a substantial range of affine distortion,addition of noise,and change in illumination.Its fast algorithm also is provided,that can substitute all multiplicative operations with shift operations for the Laplacian of Gaussian smoothing.The Laplace-SUSAN detector has a lot more corners than other detectors,so applied to SIFT it can perform more excellent for small object recogni- tion.