그림 1. SIFT DoG 피라미드 생성 과정 Fig. 1. The process to form a SIFT DoG pyramid
그림 2. SIFT 극점 추출 과정 Fig. 2. SIFT extrema extraction process
그림 3. 옥타브를 0으로 설정하여 추출한 SIFT 특징들 Fig. 3. SIFT features extracted with octave set to 0
그림 4. 밝기 정도를 변화시킨 영상의 예; (a) +25, (b) +50, (c) +75, (d) +100 Fig. 4. Image examples with varying brightness level; (a) +25, (b) +50, (c) +75, (d) +100
그림 5. 흐림 정도를 변화시킨 영상의 예; (a) 원본, (b) 반경 0.5, (c) 반경 1.0, (d) 반경 1.5, (e) 반경 2.0, (f) 반경 2.5 Fig. 5. Example Images with varying blur level; (a) original, (b) radius 0.5, (c) radius 1.0, (d) radius 1.5, (e) radius 2.0, (f) radius 2.5
그림 6. 왜곡된 영상의 특징점 반복성 측정결과; (a) 밝기 변화, (b) 흐림 정도 변화 Fig. 6. Results of the feature point repeatability measure for the distorted images; (a) change in brightness, (b) change in blur
표 1. 제안한 DNN 구성 Table 1. Configurations of the proposed DNNs
표 2. 제안한 DNN의 실험결과 Table 2. Experimental results for the proposed DNN
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