Image segmentation and object recognition based on bidirectional scanning fusion technique

2009 ◽  
Author(s):  
Hao-peng Xu ◽  
Wuqin Toing ◽  
Wei-liang Fan ◽  
Jin-yu Xiong
2011 ◽  
Vol 12 (4) ◽  
pp. 1423-1433 ◽  
Author(s):  
Yousun Kang ◽  
Koichiro Yamaguchi ◽  
Takashi Naito ◽  
Yoshiki Ninomiya

2008 ◽  
Vol 25 (5-6) ◽  
pp. 685-691 ◽  
Author(s):  
MURIEL BOUCART ◽  
PASCAL DESPRETZ ◽  
KATRINE HLADIUK ◽  
THOMAS DESMETTRE

AbstractMost studies on people with age-related macular degeneration (AMD) have been focused on investigations of low-level processes with simple stimuli like gratings, letters, and in perception of isolated faces or objects. We investigated the ability of people with low vision to analyze more complex stimuli like photographs of natural scenes. Fifteen participants with AMD and low vision (acuity on the better eye <20/200) and 11 normally sighted age-matched controls took part in the study. They were presented with photographs of either colored or achromatic gray level scenes in one condition and with photographs of natural scenes versus isolated objects extracted from these scenes in another condition. The photographs were centrally displayed for 300 ms. In both conditions, observers were instructed to press a key when they saw a predefined target (a face or an animal). The target was present in half of the trials. Color facilitated performance in people with low vision, while equivalent performance was found for colored and achromatic pictures in normally sighted participants. Isolated objects were categorized more accurately than objects in scenes in people with low vision. No difference was found for normally sighted observers. The results suggest that spatial properties that facilitate image segmentation (e.g., color and reduced crowding) help object perception in people with low vision.


1985 ◽  
Vol 18 (1) ◽  
pp. 73-87 ◽  
Author(s):  
Hon-Son Don ◽  
King-Sun Fu

2014 ◽  
Vol 602-605 ◽  
pp. 1680-1683
Author(s):  
Zhan Peng Wang ◽  
Jian Dong Tian ◽  
Yan Dong Tang ◽  
Yan Zhu Zhang ◽  
Yong Xia ◽  
...  

Shadows may cause many problems in computer vision, such as object recognition, image segmentation and video surveillance. In this paper, we present a new method to detect cast shadow in a single outdoor image. We build up an illumination model to explain the process of shadow formed, and through this model we introduce some useful features. The regions for extract features are acquired through canny edge detector, after a series of morphological operations. Then we use SVM classifier with a multi-kernel model to train these features for shadow region classification. Our results show that edges of shadow images can be detected effectively with our methods.


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