A marked bounding box method for image data reduction and reconstruction of sole patterns

2012 ◽  
Author(s):  
Xingyue Wang ◽  
Jianhua Wu ◽  
Qingmin Zhao ◽  
Jian Cheng ◽  
Yican Zhu
Keyword(s):  
Data Reduction ◽  
Image Data ◽  
Bounding Box ◽  
Box Method

Generation of Geometric Measurement Collision-Free Path for Curved Part

2013 ◽  
Vol 421 ◽  
pp. 427-432
Author(s):  
Fu Ji Wang ◽  
Zhen Yuan Jia ◽  
Ming Xing Li ◽  
Jian Wei Ma ◽  
Lei Ding
Keyword(s):  
Extreme Points ◽  
Complex Surface ◽  
Surface Shape ◽  
Surface Intersection ◽  
Bounding Box ◽  
Measuring Surface ◽  
Security Problem ◽  
Box Method ◽  
Measurement Path ◽  
Geometric Measurement

Collision between the contact probe and the measuring part will occur easily when conducting geometric measurement of the curved parts with complex surface shape. To solve the security problem of geometric measurement, a generation method of collision-free measurement path was proposed. First, collision check was simplified into the calculation of line-surface intersection. Meanwhile, we used bounding box method and triangulation method as auxiliary tools. Then, when dealing with collision avoidance, we utilized bounding box in parametric directions to avoid collisions caused by neighboring surfaces. In addition, we used parameter extreme points to avoid collisions caused by the measuring surface itself. At last, path simulation of a complex curved part verifies the security of the path generated by means of the method proposed in this paper.

Impact of data reduction on multivariate classification models built on spectral data from bio-samples

2015 ◽  
Vol 30 (5) ◽  
pp. 1117-1127 ◽  
Author(s):  
Anders Larsson ◽  
Henrik Andersson ◽  
Lars Landström
Keyword(s):  
Spectral Data ◽  
Data Reduction ◽  
Image Data ◽  
Classification Models ◽  
Multivariate Classification

Multivariate classification models, both from 1D spectra and 2D image data (also with simulated shifts), were evaluated and compared.

scholarly journals Segmentation Comparing Eggs Watermarking Image and Original Image

2017 ◽  
Vol 6 (1) ◽  
pp. 47-53
Author(s):  
Anton Yudhana ◽  
Sunardi Sunardi ◽  
Shoffan Saifullah
Keyword(s):  
Image Processing ◽  
Small Area ◽  
Image Data ◽  
Watermark Image ◽  
Original Image ◽  
Segmentation Method ◽  
Bounding Box ◽  
Chicken Eggs ◽  
The Impact

The research used watermarking techniques to obtain the image originality. The aims of the research were to identify small area in eggs properly and compared preprocessing, the methods, and the results of image processing. The study has been improved from the previous papers by combined all methods and analysis was obtained.This study was conducted by using centroid and the bounding box for determining the object and the small area of chicken eggs. The segmentation method was used to compare the original image and the watermarked image. Image processing using image data that are subject watermark to maintain the authenticity of the images used in the study will the impact in delivering the desired results. In the identification of chicken eggs using watermark image using several methods are expected to provide results as desired. Segmentation also deployed to process the Image and counted the objects. The results showed that the process of segmentation and objects counting determined that the original image and watermarked image had the same value and recognized eggs. Identification had determined percentage of 100% for all the samples.

scholarly journals A Safety Warning Algorithm Based on Axis Aligned Bounding Box Method to Prevent Onsite Accidents of Mobile Construction Machineries

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7075
Author(s):  
Cynthia Changxin Wang ◽  
Mudan Wang ◽  
Jun Sun ◽  
Mohammad Mojtahedi
Keyword(s):  
Safety Management ◽  
Soft Soil ◽  
Safety Monitoring ◽  
Human Beings ◽  
Risk Area ◽  
Foundation Pit ◽  
Bounding Box ◽  
Safety Warning ◽  
Risk Areas ◽  
Box Method

Mobile construction machineries are accident-prone on a dynamic construction site, as the site environment is constantly changing and continuous safety monitoring by human beings is impossible. These accidents usually happen in the form of machinery overturning or collapsing into risk areas, including the foundation pit, slopes, or soft soil area. Therefore, preventing mobile construction machineries from entering risk areas is the key. However, currently, there is a lack of practical safety management techniques to achieve this. Utilizing a wireless sensor device to collect the location information of mobile construction machineries, this research develops a safety warning algorithm to prevent the machineries moving into risk area and reduces onsite overturning or collapsing accidents. A modified axis aligned bounding box method is proposed according to the movement patterns of mobile construction machineries, and the warning algorithm is developed based on the onsite safety management regulations. The algorithm is validated in a real case simulation when machinery enters the warning zone. The simulation results showed that the overall algorithm combining the location sensing technology and the modified bounding box method could detect risk and give warnings in a timely manner. This algorithm can be implemented for the safety monitoring of mobile construction machineries in daily onsite management.

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