CAJ | 학술논문

视觉词典容量是影响图像场景分类精度的重要因素之一，大容量的视觉词典因计算量较大影响了分类的效率，而小容量的视觉词典由于多义词问题的严重致使场景分类精度降低。针对该问题，提出一种基于概念格层次分析的视觉词典生成方法。首先生成关于训练图像视觉词包模型的初始视觉词典；然后在构造的概念格上利用概念格的概念层次性，通过动态地调整外延数阈值，获取粒度大小不同容量的描述图像各场景语义的约简视觉词典；最后对各类约简视觉单词构成向量进行异或，删除多义词，进而生成有效描述图像场景语义的视觉词典。实验结果表明，文中方法是有效的。
시각사전용량시영향도상장경분류정도적중요인소지일，대용량적시각사전인계산량교대영향료분류적효솔，이소용량적시각사전유우다의사문제적엄중치사장경분류정도강저。침대해문제，제출일충기우개념격층차분석적시각사전생성방법。수선생성관우훈련도상시각사포모형적초시시각사전；연후재구조적개념격상이용개념격적개념층차성，통과동태지조정외연수역치，획취립도대소불동용량적묘술도상각장경어의적약간시각사전；최후대각류약간시각단사구성향량진행이혹，산제다의사，진이생성유효묘술도상장경어의적시각사전。실험결과표명，문중방법시유효적。
The visual dictionary size is an important factor that affects the performance of scene classifica-tion. The large capacity of visual dictionary can influence the classification efficiency due to the lager cal-culation, while the small capacity of visual dictionary can reduce the classification accuracy because of the influences of polysemy. To solve the problem, a generating method of visual dictionary based on the concept lattice hierarchy is proposed in this paper. First, the initial visual dictionary of training images on bag-of-visterms model is generated. Then, with the use of concept lattice’s hierarchy analysis, the different granularities of reduced visual dictionaries are extracted from the concept lattice by setting different exten-sion thresholds. Finally, the polysemy is deleted by making XOR operations on all types of the reduced vis-ual dictionaries, and a visual dictionary for better describing the image content is generated. Experimental results show that this method is effective.