An IoT based modified graph cut segmentation with optimized adaptive connectivity and shape priors

2020 ◽  
Vol 28 ◽  
pp. 100249 ◽  
Author(s):  
Adonu Celestine ◽  
J. Dinesh Peter
Author(s):  
Yang Yu ◽  
Yasushi Makihara ◽  
Yasushi Yagi

AbstractWe address a method of pedestrian segmentation in a video in a spatio-temporally consistent way. For this purpose, given a bounding box sequence of each pedestrian obtained by a conventional pedestrian detector and tracker, we construct a spatio-temporal graph on a video and segment each pedestrian on the basis of a well-established graph-cut segmentation framework. More specifically, we consider three terms as an energy function for the graph-cut segmentation: (1) a data term, (2) a spatial pairwise term, and (3) a temporal pairwise term. To maintain better temporal consistency of segmentation even under relatively large motions, we introduce a transportation minimization framework that provides a temporal correspondence. Moreover, we introduce the edge-sticky superpixel to maintain the spatial consistency of object boundaries. In experiments, we demonstrate that the proposed method improves segmentation accuracy indices, such as the average and weighted intersection of union on TUD datasets and the PETS2009 dataset at both the instance level and semantic level.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Kazeem Oyeyemi Oyebode ◽  
Shengzhi Du ◽  
Barend Jacobus van Wyk ◽  
Karim Djouani

Graph cut segmentation provides a platform to analyze images through a global segmentation strategy, and as a result of this, it has gained a wider acceptability in many interactive and automatic segmentation fields of application, such as the medical field. The graph cut energy function has a parameter that is tuned to ensure that the output is neither oversegmented (shrink bias) nor undersegmented. Models have been proposed in literature towards the improvement of graph cut segmentation, in the context of interactive and automatic cell segmentation. Along this line of research, the graph cut parameter has been leveraged, while in some instances, it has been ignored. Therefore, in this work, the relevance of graph cut parameter on both interactive and automatic cell segmentation is investigated. Statistical analysis, based on F1 score, of three publicly available datasets of cells, suggests that the graph cut parameter plays a significant role in improving the segmentation accuracy of the interactive graph cut than the automatic graph cut.


2021 ◽  
Vol 40 (1) ◽  
pp. 53-63
Author(s):  
Xin Sun ◽  
Dong Li ◽  
Wei Wang ◽  
Hongxun Yao ◽  
Dongliang Xu ◽  
...  

 We present a novel graph cut method for iterated segmentation of objects with specific shape bias (SBGC). In contrast with conventional graph cut models which emphasize the regional appearance only, the proposed SBGC takes the shape preference of the interested object into account to drive the segmentation. Therefore, the SBGC can ensure a more accurate convergence to the interested object even in complicated conditions where the appearance cues are inadequate for object/background discrimination. In particular, we firstly evaluate the segmentation by simultaneously considering its global shape and local edge consistencies with the object shape priors. Then these two cues are formulated into a graph cut framework to seek the optimal segmentation that maximizing both of the global and local measurements. By iteratively implementing the optimization, the proposed SBGC can achieve joint estimation of the optimal segmentation and the most likely object shape encoded by the shape priors, and eventually converge to the candidate result with maximum consistency between these two estimations. Finally, we take the ellipse shape objects with various segmentation challenges as examples for evaluation. Competitive results compared with state-of-the-art methods validate the effectiveness of the technique.


2020 ◽  
Vol 17 (9) ◽  
pp. 4394-4397
Author(s):  
Bhawna Nigam ◽  
Anvika Sharma ◽  
B. Basavaprasad ◽  
M. Niranjanamurthy

Rice botanically belongs to Oryza sativa L. of Gramineae family. Rice is the significant principal foods for almost majority of the world’s population and impacts the livelihood and economy of many billion people. Though there are many well established techniques such as electronic devices, sensors, biosensors or high end instruments to study the different chemical components, sample preparation, specificity, sensitivity, accuracy and reusable issues. In order to overcome such issues, an alternate technique or method need to be developed which can replace the human intervention to avoid the experimental errors through analyzing the surface structure rather than the chemical method. Among the different changes that occurred during the ageing process, internal structure is also an important phenomenon because of the starch modification with several factors like temperature, moisture content and storage period. Hence, the objective of the study concentrates on the analyzing the structural changes to assess the age of rice through fuzzy and graph cut segmentation technique.


2018 ◽  
Vol 77 (21) ◽  
pp. 28905-28923 ◽  
Author(s):  
Haijiang Zhu ◽  
Zhanhong Zhuang ◽  
Jinglin Zhou ◽  
Xuejing Wang ◽  
Wenhua Xu

Sign in / Sign up

Export Citation Format

Share Document