Modified SIFT descriptor and key-point matching for fast and robust image mosaic
Modified SIFT descriptor and key-point matching for fast and robust image mosaic

To improve the performance of the scale invariant feature transform (SIFT), a modified SIFT (M-SIFT) descriptor is proposed to realize fast and robust key-point extraction and matching. In descriptor generation, 3 rotation-invariant concentric-ring grids around the key-point location are used instead of 16 square grids used in the original SIFT. Then, 10 orientations are accumulated for each grid, which results in a 30-dimension descriptor. In descriptor matching, rough rejection mismatches is proposed based on the difference of grey information between matching points. The performance of the proposed method is tested for image mosaic on simulated and real-world images. Experimental results show that the M-SIFT descriptor inherits the SIFT's ability of being invariant to image scale and rotation, illumination change and affine distortion. Besides the time cost of feature extraction is reduced by 50% compared with the original SIFT. And the rough rejection mismatches can reject at least 70% of mismatches. The results also demonstrate that the performance of the proposed M-SIFT method is superior to other improved SIFT methods in speed and robustness.
To improve the performance of the scale invariant feature transform (SIFT), a modified SIFT (M-SIFT) descriptor is proposed to realize fast and robust key-point extraction and matching. In descriptor generation, 3 rotation-invariant concentric-ring grids around the key-point location are used instead of 16 square grids used in the original SIFT. Then, 10 orientations are accumulated for each grid, which results in a 30-dimension descriptor. In descriptor matching, rough rejection mismatches is proposed based on the difference of grey information between matching points. The performance of the proposed method is tested for image mosaic on simulated and real-world images. Experimental results show that the M-SIFT descriptor inherits the SIFT's ability of being invariant to image scale and rotation, illumination change and affine distortion. Besides the time cost of feature extraction is reduced by 50% compared with the original SIFT. And the rough rejection mismatches can reject at least 70% of mismatches. The results also demonstrate that the performance of the proposed M-SIFT method is superior to other improved SIFT methods in speed and robustness.