Image retrieval for identification of insects based on saliency map and distance metric learning

Susumu Genma, Takahiro Ogawa, M. Haseyama
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引用次数: 4

Abstract

This paper presents an image retrieval method for insect identification based on saliency map and distance metric learning. First, the proposed method extracts regions of insects from target images by using saliency map and calculates visual features from the extracted insect regions. Next, in order to realize accurate retrieval of insects based on the calculated features, distance metric learning is newly adopted. Consequently, through users' evaluation in the retrieval, optimal distance can be obtained for the calculated visual features to obtain successful retrieval results, and the identification of insects becomes feasible. Experimental results show the effectiveness of our method.
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基于显著性图和距离度量学习的昆虫识别图像检索
提出了一种基于显著性图和距离度量学习的昆虫识别图像检索方法。该方法首先利用显著性图从目标图像中提取昆虫区域,并对提取的昆虫区域进行视觉特征计算;其次,为了实现基于计算特征的昆虫精确检索,采用了距离度量学习方法。因此,通过用户在检索中的评价,可以为计算的视觉特征获得最优距离,从而获得成功的检索结果,从而使昆虫的识别变得可行。实验结果表明了该方法的有效性。
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