Color-blob-based COSFIRE filters for object recognition

作者：

Highlights：

• We propose novel color-blob-based COSFIRE filters.

• They are effective for recognizing also objects with diffuse region boundaries.

• Such a filter models (a part of) an object by a specific arrangement of color blobs.

• The blobs contain information about the sizes and colors of the interior of regions.

• We achieve high recognition rates: GTSRB (98.94%) and butterfly (89.02%) data sets.

摘要

•We propose novel color-blob-based COSFIRE filters.•They are effective for recognizing also objects with diffuse region boundaries.•Such a filter models (a part of) an object by a specific arrangement of color blobs.•The blobs contain information about the sizes and colors of the interior of regions.•We achieve high recognition rates: GTSRB (98.94%) and butterfly (89.02%) data sets.

论文关键词：Object recognition,Object representation,Color,Feature extraction,Trainable filters

论文评审过程：Received 25 September 2015, Revised 9 September 2016, Accepted 4 October 2016, Available online 15 November 2016, Version of Record 28 December 2016.

论文官网地址：https://doi.org/10.1016/j.imavis.2016.10.006