CAJ | 학술논문

提出了一种采用小波变换对复杂动态背景变化程度的检测方法.对红外序列图像进行小波变换预处理后,可以提取出若干个特征区域,通过检测这些特征区域的差异来判断背景的变化程度,实现背景抑制.在抑制动态背景的基础之上,运用基于动态先验知识的区域主动轮廓模型的水平集方法来实现红外多目标的数据关联和跟踪,动态先验知识包括形状描述因子、灰度特征和运动特征等.同时,在多目标跟踪中存在目标"合并和分裂"的现象,运用"记忆和填充"方法来实现对多目标的稳定跟踪.通过对实际复杂动态背景条件下的红外序列图像进行多目标跟踪和检测实验,验证了所提方法的可行性和有效性.
제출료일충채용소파변환대복잡동태배경변화정도적검측방법.대홍외서렬도상진행소파변환예처리후,가이제취출약간개특정구역,통과검측저사특정구역적차이래판단배경적변화정도,실현배경억제.재억제동태배경적기출지상,운용기우동태선험지식적구역주동륜곽모형적수평집방법래실현홍외다목표적수거관련화근종,동태선험지식포괄형상묘술인자、회도특정화운동특정등.동시,재다목표근종중존재목표"합병화분렬"적현상,운용"기억화전충"방법래실현대다목표적은정근종.통과대실제복잡동태배경조건하적홍외서렬도상진행다목표근종화검측실험,험증료소제방법적가행성화유효성.
An efficient approach based on wavelet transform is presented to detect the variation degree of dynamic background. Firstly, some candidate regions can be obtained by processing IR data through wavelet transform, then the degree of the difference between current and referenced background can be judged through detecting the difference of the above feature regions. Finally, some small moving candidate targets can bedetected by eliminating background. After eliminating background, data association and robust tracking of those targets can be realized by level set tracking method based on region-based active contour with dynamic priors. Dynamic priors include shape descriptor, intensity information, moving features and etc. In addition, targets' merging and splitting phenomena occasionally arise during multi-target tracking. This problem can be solved by 'memorizing and filling'. The proposed approach is validated to track multi-target effectively by using actual infrared image sequences with complex dynamic background. Experiment results indicate the feasibility and effectiveness of the proposed method.