计算机辅助设计与图形学学报
計算機輔助設計與圖形學學報
계산궤보조설계여도형학학보
JOURNAL OF COMPUTER-AIDED DESIGN & COMPUTER GRAPHICS
2015年
4期
666-673
,共8页
崔明明%闫镔%曹鸿涛%陈健%曾磊
崔明明%閆鑌%曹鴻濤%陳健%曾磊
최명명%염빈%조홍도%진건%증뢰
三维图像拼接%全局二值特征描述子%相似特征匹配
三維圖像拼接%全跼二值特徵描述子%相似特徵匹配
삼유도상병접%전국이치특정묘술자%상사특정필배
3D image mosaic%global binary descriptor%similar feature matching
三维图像拼接是通过锥束CT (CBCT)获取大尺寸物体完整的高分辨率三维图像过程中的关键技术之一,成为目前三维图像处理的一个新的研究方向。针对基于特征点的三维 CBCT 图像拼接技术中相似特征匹配正确率低、匹配过程耗时长的问题,提出一种基于全局二值特征描述子的三维 CBCT 图像快速匹配算法。首先对二值特征描述子 BRIEF 进行三维拓展,以适应三维图像;在此基础上加入全局描述子,增强特征描述子的独特性;在特征点匹配时,根据上述特征描述子的特点设计由粗到精的匹配策略,提高特征匹配正确率和效率。实验结果表明,该算法简单有效,可以在大量相似特征条件下提高特征点匹配的正确率,同时也显著提升了匹配速度。
三維圖像拼接是通過錐束CT (CBCT)穫取大呎吋物體完整的高分辨率三維圖像過程中的關鍵技術之一,成為目前三維圖像處理的一箇新的研究方嚮。針對基于特徵點的三維 CBCT 圖像拼接技術中相似特徵匹配正確率低、匹配過程耗時長的問題,提齣一種基于全跼二值特徵描述子的三維 CBCT 圖像快速匹配算法。首先對二值特徵描述子 BRIEF 進行三維拓展,以適應三維圖像;在此基礎上加入全跼描述子,增彊特徵描述子的獨特性;在特徵點匹配時,根據上述特徵描述子的特點設計由粗到精的匹配策略,提高特徵匹配正確率和效率。實驗結果錶明,該算法簡單有效,可以在大量相似特徵條件下提高特徵點匹配的正確率,同時也顯著提升瞭匹配速度。
삼유도상병접시통과추속CT (CBCT)획취대척촌물체완정적고분변솔삼유도상과정중적관건기술지일,성위목전삼유도상처리적일개신적연구방향。침대기우특정점적삼유 CBCT 도상병접기술중상사특정필배정학솔저、필배과정모시장적문제,제출일충기우전국이치특정묘술자적삼유 CBCT 도상쾌속필배산법。수선대이치특정묘술자 BRIEF 진행삼유탁전,이괄응삼유도상;재차기출상가입전국묘술자,증강특정묘술자적독특성;재특정점필배시,근거상술특정묘술자적특점설계유조도정적필배책략,제고특정필배정학솔화효솔。실험결과표명,해산법간단유효,가이재대량상사특정조건하제고특정점필배적정학솔,동시야현저제승료필배속도。
3D image mosaic is a crucial technology to obtain the whole high-resolution image of large-size object by cone beam computed tomography (CBCT) system, which has become a new research direction of 3D image processing. Aiming at the low matching accuracy of similar features and the time-consuming of feature matching process, we propose a fast feature matching algorithm based on global binary descriptor. The method firstly ex-tends the original BRIEF (Binary robust independent elementary features descriptor) to the 3D case to suit 3D images. Then a global binary descriptor is added to it to enhance the discrimination of the 3D extended feature descriptor. Finally, according to the characteristics of feature descriptor mentioned above, a coarse-to-fine feature matching strategy is designed to improve the accuracy and efficiency of feature matching. Experiments show that the proposed method is simple and effective, which can bring down the number of mismatches and improve the matching speed obviously.