Contour Segment Matching by Integrating Intra and Inter Shape Cues of Objects

2009 ◽  
Author(s):  
Ishani Chakraborty ◽  
Ahmed Elgammal
Keyword(s):  
Contour Segment ◽  
Segment Matching

Shape-based object retrieval by contour segment matching

2014 ◽  
Author(s):  
Cong Yang ◽  
Oliver Tiebe ◽  
Pit Pietsch ◽  
Christian Feinen ◽  
Udo Kelter ◽  
...  
Keyword(s):  
Object Retrieval ◽  
Contour Segment ◽  
Segment Matching

Deformed contour segment matching for multi-source images

2021 ◽  
pp. 107968
Author(s):  
Quan Wu ◽  
Guili Xu ◽  
Yuehua Cheng ◽  
Zhengsheng Wang ◽  
Zhenhua Li
Keyword(s):  
Contour Segment ◽  
Segment Matching

RECOGNIZING HANDWRITTEN CHINESE CHARACTERS BY STROKE-SEGMENT MATCHING USING AN ITERATION SCHEME

1991 ◽  
Vol 05 (01n02) ◽  
pp. 175-197 ◽  
Author(s):  
SHENG-LIN CHOU ◽  
WEN-HSIANG TSAI
Keyword(s):  
Character Recognition ◽  
Contextual Information ◽  
Recognition Rate ◽  
Stable State ◽  
Evaluation Process ◽  
Iteration Scheme ◽  
Chinese Characters ◽  
Structure Information ◽  
Segment Matching ◽  
Set Up

The problem of handwritten Chinese character recognition is solved by matching character stroke segments using an iteration scheme. Length and orientation similarity properties, and coordinate overlapping ratios are used to define a measure of similarity between any two stroke segments. The initial measures of similarity between the stroke segments of the input and template characters are used to set up a match network which includes all the match relationships between the input and template stroke segments. Based on the concept of at-most-one to one mapping an iteration scheme is employed to adjust the match relationships, using the contextual information implicitly contained in the match network, so that the match relationships can get into a stable state. From the final match relationships, matched stroke-segment pairs are determined by a mutually-best match strategy and the degree of similarity between the input and each template character is evaluated accordingly. Certain structure information of Chinese characters is also used in the evaluation process. The experimental results show that the proposed approach is effective. For recognition of Chinese characters written by a specific person, the recognition rate is about 96%. If the characters of the first three ranks are checked in counting the recognition rate, the rate rises to 99.6%.

Accurate Camera Pose Estimation for KinectFusion Based on Line Segment Matching by LEHF

2014 ◽  
Author(s):  
Yusuke Nakayama ◽  
Toshihiro Honda ◽  
Hideo Saito ◽  
Masayoshi Shimizu ◽  
Nobuyasu Yamaguchi
Keyword(s):  
Pose Estimation ◽  
Line Segment ◽  
Camera Pose Estimation ◽  
Line Segment Matching ◽  
Camera Pose ◽  
On Line ◽  
Segment Matching

Smoothly varying projective transformation for line segment matching

2022 ◽  
Vol 183 ◽  
pp. 129-146
Author(s):  
Xianwei Zheng ◽  
Zhuang Yuan ◽  
Zhen Dong ◽  
Mingyue Dong ◽  
Jianya Gong ◽  
...  
Keyword(s):  
Line Segment ◽  
Projective Transformation ◽  
Line Segment Matching ◽  
Segment Matching

Contour segment grouping for object detection

2017 ◽  
Vol 48 ◽  
pp. 292-309 ◽  
Author(s):  
Hui Wei ◽  
Chengzhuan Yang ◽  
Qian Yu
Keyword(s):  
Object Detection ◽  
Contour Segment

scholarly journals Object Detection by Contour Segment Networks

2006 ◽  
pp. 14-28 ◽  
Author(s):  
Vittorio Ferrari ◽  
Tinne Tuytelaars ◽  
Luc Van Gool
Keyword(s):  
Object Detection ◽  
Contour Segment
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