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Article | 01-April-2018

A New Connected-Component Labeling Algorithm

This paper proposes a new first-scan method for two-scan labeling algorithms. In the first scan, our proposed method first scans image lines three by three with a leaving line, and for foreground pixels among each three lines, assigns them provisional labels, and finds and resolves label equivalences among them. Then, it processes the leaving lines from top to bottom one by one, and for each line, assigns foreground pixels on the line provisional labels, finding and resolving label equivalences

Yuyan Chao, Lifeng He, Kenji Suzuki, Qian Yu, Wei Tang

International Journal of Advanced Network, Monitoring and Controls, Volume 1 , ISSUE 1, –

Article | 01-June-2016

A HYBRID FUZZY MORPHOLOGY AND CONNECTED COMPONENTS LABELING METHODS FOR VEHICLE DETECTION AND COUNTING SYSTEM

A hybrid fuzzy morphology and connected components labeling method is proposed for detecting and counting the number of vehicles in an image taken from a traffic monitoring camera. A fuzzy morphology approach in image segmentation method is used in the system to achieve faster computation time compared to the supervised learning. The connected components labeling method is combined with a fuzzy morphology method to determine the region and number of objects in an image. The processing phases in

Chastine Fatichah, Joko Lianto Buliali, Ahmad Saikhu, Silvester Tena

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 765–779

Research paper | 10-April-2013

Labeling of Human Motion Based on CBGA and Probabilistic Model

In this paper, we present a novel method for the labeling of human motion which uses Constraint-Based Genetic Algorithm (CBGA) to optimize the probabilistic model of body features and construct the set of conditional independence relations among the body features by a fitness function. The approach also allows the user to add custom rules to produce valid candidate solutions to achieve more accurate results with constraint-based genetic operators. Specifically, we design the fitness function

Fuyuan Hu, Hau San Wong

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 2, 583–609

Article | 01-April-2020

ISBT 128 blood labeling: introduction and reference laboratory applications  

Suzanne H. Butch, Patricia B. Distler

Immunohematology, Volume 22 , ISSUE 1, 30–36

research-article | 30-November-2019

A novel approach to label road defects in video data: semi-automated video analysis

map road defects in a semi-automated fashion. Karlsruhe Institute of Technology (KIT) has developed an elegant method (Masino et al., 2017) to create training data sets of images for road damage classification3. The efficiency gains in terms of accuracy and time savings of event labeling have operational and commercial benefits. To detect potholes on rural roads in Northland4 (NZ) at present, a highly trained road safety engineer travels the 5,000 km long road network every month at an average

Jakob Thumm, Johannes Masino, Martin Knoche, Frank Gauterin, Markus Reischl

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–9

research-article | 30-November-2018

Cell-based immunofluorescence assay for screening the neurogenesis potential of new drugs in adult hippocampal neural progenitor cells

be used to detect neurogenesis, including in vivo and in vitro labeling with the thymidine analogue, bromodeoxyuridine (BrdU), endogenous cell-cycle markers, and cell stage and lineage commitment markers (Kuhn et al., 2016). Each method has its own strengths and limitations; however, when several compounds require quick screening to determine whether they promote neurogenesis, these methods may be unsuitable as they require several reagents and are time-consuming. Therefore, we propose a cell

Kun Zhang, Bin Li, Peifang Li, Xiaoli Yang, Huixian Cui, Xiaoyun Liu

Acta Neurobiologiae Experimentalis, Volume 79 , ISSUE 3, 303–309

Review | 01-April-2020

Labeling of cell therapy products: a review of the past and a look into the future

N. Rebecca Haley, John P. Miller

Immunohematology, Volume 23 , ISSUE 2, 63–68

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