Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 303-308, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-303-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 303-308, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-303-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

EDGE-BASED LOCALLY AGGREGATED DESCRIPTORS FOR IMAGE CLUSTERING

Y. Dong, D. Fan, Q. Ma, S. Ji, and R. Lei Y. Dong et al.
  • Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China

Keywords: Edge feature points, Local feature aggregation, Global image descriptors, Image clustering

Abstract. The current global image descriptors are mostly obtained by using the local image features aggregation, which fail to take full account of the details of the image, resulting in the loss of the semantic content information. It cannot be well used to make a good distinction between the high similarity images. In this paper, a new method of image representation, which can express the whole semantics and detail features of the image, is proposed by combining the edge features of the image. It is used to make a global description of the images and then clustering. The experimental results show that the proposed method is capable of clustering of the similarity images with high accuracy and low error rate.