Abstract
Since traditional partition approach may construct very different image representation because of the changed locations of objects in the same image, a subblock partition of multi-layer pattern method for image representation is proposed. The saliency windows straddled by superpixels are utilized to partition the image into multi-layer pattern subblocks. Then all the subblocks are combined to a three order tensor. Comparing to the results of image classification item of Pascal Voc 2007 Challenge，it indicates that the proposed representation method is robust to the varied object locations and achieves better performance than other approaches. CCS Concepts Computing methodologies➝Computer vision • Computing methodologies➝ Machine learning
Highlights
Accurate depiction of the pattern information in the image is the premise to realization of the accurate description and classif-ication of the image
With more position information than the SPM method, it shows some robustness to the rotation transformation in the image, but this method focuses more on the "linear" and "rotating" distribution of the image, and fails to fully reflect the various transformations that exist in the image
In order to better express the information in an image, this paper proposes a new partitioning method for image subblock partition: image multi-layer pattern subblock partition
Summary
1.Chongqing Land Resources Housing Surveying and Planning Institute 2. School of Remote Sensing and Information Engineering, Wuhan University Huangshandadao Road No.64, yubei, Chongqing, China +86 13668093020 Chongqing Land Resources Housing Surveying and Planning Institute Huangshandadao Road No.64, yubei, Chongqing, China +86 13896829668 Chongqing industrial& commercial school baisha, jiangjin, Chongqing, China +86 13618381908
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
