Shape-based detection of Maya hieroglyphs using weighted bag representations
作者：
Highlights：
• A uniform sampling improves detection results compared to the DoG point detector.
• The previous observation is consistent with the previous works on grayscale images.
• A medium-to-small size of characteristic scale is best for shape detection.
• The HOOSC method outperforms the SIFT descriptor for description of binary images.
• The proposed weighted bag representation is suitable for shape-based object detection.
摘要
Highlights•A uniform sampling improves detection results compared to the DoG point detector.•The previous observation is consistent with the previous works on grayscale images.•A medium-to-small size of characteristic scale is best for shape detection.•The HOOSC method outperforms the SIFT descriptor for description of binary images.•The proposed weighted bag representation is suitable for shape-based object detection.
论文关键词：Shape-based object detection,Binary images,Bag-of-words,Maya hieroglyphs
论文评审过程：Received 30 December 2013, Revised 11 May 2014, Accepted 11 June 2014, Available online 19 June 2014.
论文官网地址：https://doi.org/10.1016/j.patcog.2014.06.009
