- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Fish swarm intelligent to optimize real time monitoring of chips drying using machine vision
摘要： This study attempted to apply machine vision-based chips drying monitoring system which is able to optimise the drying process of cassava chips. The objective of this study is to propose fish swarm intelligent (FSI) optimization algorithms to find the most significant set of image features suitable for predicting water content of cassava chips during drying process using artificial neural network model (ANN). Feature selection entails choosing the feature subset that maximizes the prediction accuracy of ANN. Multi-Objective Optimization (MOO) was used in this study which consisted of prediction accuracy maximization and feature-subset size minimization. The results showed that the best feature subset i.e. grey mean, L(Lab) Mean, a(Lab) energy, red entropy, hue contrast, and grey homogeneity. The best feature subset has been tested successfully in ANN model to describe the relationship between image features and water content of cassava chips during drying process with R2 of real and predicted data was equal to 0.9.
关键词： feature selection,machine vision,fish swarm intelligent,chips drying,artificial neural network
更新于2025-09-10 09:29:36
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[IEEE 2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE) - Huhhot, China (2018.9.14-2018.9.16)] 2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE) - Research on Image Preprocessing of Silkworm Cocoon Based on Machine Vision
摘要： In the past few years, silkworm cocoon image detection has been artificially degenerated, and it is the focus of recent years for how to use mechanized large-scale detection of cocoon mass. In the research, machine vision, as a detection method, is applied in silkworm cocoon detection; and the acquired silk cocoon image is processed and analyzed through the methods of binarization, machine vision, and LabVIRW. The effective identification of defective cocoons and the effective identification of cocoons and normal cocoons can be realized.
关键词： silkworm cocoon detection,machine vision,LabVIEW
更新于2025-09-10 09:29:36
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Development of six-DOF welding robot with machine vision
摘要： The application of machine vision to industrial robots is a hot topic in robot research nowadays. A welding robot with machine vision had been developed, which is convenient and flexible to reach the welding point with six degrees-of-freedom (DOF) manipulator, while the singularity of its movement trail is prevented, and the stability of the mechanism had been fully guaranteed. As the precise industry camera can capture the optical feature of the workpiece to reflect in the camera’s CCD lens, the workpiece is identified and located through a visual pattern recognition algorithm based on gray scale processing, on the gradient direction of edge pixel or on geometric element so that high-speed visual acquisition, image preprocessing, feature extraction and recognition, target location are integrated and hardware processing power is improved. Another task is to plan control strategy of control system, and the upper computer software is programmed in order that multi-axis motion trajectory is optimized and servo control is accomplished. Finally, prototype was developed and validation experiments show that the welding robot has high stability, high efficiency, high precision, even if welding joints are random and workpiece contour is irregular.
关键词： image recognition,linear structured light,Welding robot,machine vision
更新于2025-09-10 09:29:36
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A novel algorithm for tool wear online inspection based on machine vision
摘要： To inspect the tool wear condition in the process of numerical control (NC) machining for difficult-to-cut material, an online inspection system for tool wear is developed based on machine vision. With the help of MATLAB software, a self-matching algorithm is proposed according to the characteristics of tool wear images. The corresponding user-friendly graphical user interface (GUI) of the algorithm is developed. The bottom edges are separated by the adaptive connecting domain labeling to analyze wear condition of each edge. Then, each edge is arranged regularly by the improved rotatory positioning. The cutting edge is extracted by the method of partial angle threshold to fit and calculate the bottom wear value. It is shown that the absolute values of errors on the maximum wear width are less than 0.007 mm by using the self-matching algorithm. In the case of severe wear and breakage, the absolute values of errors on the maximum wear width are less than 0.057 mm because of uneven reflected light. The system features high response speed, high inspecting accuracy, and anti-noise performance. It is proved to be able to increase the utilization of cutting tools and guarantee the quality of workpiece. This method is potential to guarantee the reliability of cutting tool in aerospace manufacturing.
关键词： Image processing,Tool wear,Machine vision,Self-matching algorithm,Online inspection
更新于2025-09-10 09:29:36
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A novel surface roughness measurement method based on the red and green aliasing effect
摘要： A common requirement in many machine learning algorithms is that the training data is sufficient. However, in the visual measurement of surface roughness, this requirement often can't be meet due to the reason that it is time-consuming and expensive to process and label the training samples. To address this issue, this paper proposes a novel method to establish an advanced roughness predictive model with less standard training samples based on inductive transfer learning. The experimental results show that the proposed method has superior measurement performance, and can maintain the average relative error of 12.57% even when the training data is insufficient. This indicates that the proposed method can provide a new strategy for improving the visual roughness measurement performance.
关键词： Roughness measurement,Index design,Inductive transfer learning,Machine vision
更新于2025-09-09 09:28:46
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HW/SW co-design of a visual SLAM application
摘要： Vision-based advanced driver assistance systems (ADAS), appeared in the 2000s, are increasingly integrated on-board mass-produced vehicles, as off-the-shelf low-cost cameras are now available. But ADAS implement most of the time-specific and basic functionalities such as lane departure or control of the distance to other vehicles. Integrating accurate localization and mapping functionalities meeting the constraints of ADAS (high-throughput, low-consumption, and small-design footprint) would pave the way towards obstacle detection, identification and tracking on-board vehicles at potential high speed. While the SLAM problem has been widely addressed by the robotics community, very few embedded operational implementations can be found, and they do not meet the ADAS-related constraints. In this paper, we implement the first 3D monocular EKF-SLAM chain on a heterogeneous architecture, on a single System on Chip (SoC), meeting these constraints. In order to do so, we picked up a standard co-design method (Shaout et al. Specification and modeling of hw/sw co-design for heterogeneous embedded systems, 2009) and adapted it to the implementation of potentially any of such complex processing chains. The refined method encompasses a hardware-in-the-loop approach allowing to progressively integrate hardware accelerators on the basis of a systematic rule. We also have designed original hardware accelerators for all the image processing functions involved, and for some algebraic operations involved in the filtering process.
关键词： SLAM,ADAS,FPGA,Co-design,Machine-vision
更新于2025-09-09 09:28:46
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Automatic Pose Estimation of Uncalibrated Multi-View Images Based on a Planar Object with a Predefined Contour Model
摘要： We have presented a framework to obtain camera pose (i.e., position and orientation in the 3D space) with real scale information of the uncalibrated multi-view images and the intrinsic camera parameters automatically. Our framework consists of two key steps. First, the initial value of the intrinsic camera and the pose parameters were extracted from homography estimation based on the contour model of some planar objects. Second, a re?nement of the intrinsic camera and pose parameters was operated by the bundle adjustment procedure. Our framework can provide a complete ?ow of pose estimation of disorderly or orderly uncalibrated multi-view images, which can be used in vision tasks requiring scale information. Real multi-view images were utilized to demonstrate the robustness, ?exibility and accuracy of the proposed framework. The proposed framework was also applied in 3D reconstruction.
关键词： multi-view,homography,machine vision,pose estimation,bundle adjustment,contour model
更新于2025-09-09 09:28:46
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Using the Machine Vision Method to Develop an On-machine Insert Condition Monitoring System for Computer Numerical Control Turning Machine Tools
摘要： This study uses the machine vision method to develop an on-machine turning tool insert condition monitoring system for tool condition monitoring in the cutting processes of computer numerical control (CNC) machines. The system can identify four external turning tool insert conditions, namely fracture, built-up edge (BUE), chipping, and ?ank wear. This study also designs a visual inspection system for the tip of an insert using the surrounding light source and ?ll-light, which can be mounted on the turning machine tool, to overcome the environmental effect on the captured insert image for subsequent image processing. During image capture, the intensity of the light source changes to ensure that the test insert has appropriate surface and tip features. This study implements outer pro?le construction, insert status region capture, insert wear region judgment, and calculation to monitor and classify insert conditions. The insert image is then trimmed according to the vertical ?ank, horizontal blade, and vertical blade lines. The image of the insert-wear region is captured to monitor ?ank or chipping wear using grayscale value histogram. The amount of wear is calculated using the wear region image as the evaluation index to judge normal wear or over-wear conditions. On-machine insert condition monitoring is tested to con?rm that the proposed system can judge insert fracture, BUE, chipping, and wear. The results demonstrate that the standard deviation of the chipping and amount of wear accounts for 0.67% and 0.62%, of the average value, respectively, thus con?rming the stability of system operation.
关键词： turning machine tools,machine vision,on-machine monitoring,computer numerical control,tool insert condition
更新于2025-09-04 15:30:14
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A Novel Vision-Based Pose Measurement Method Considering the Refraction of Light
摘要： Nowadays, due to the advantages of non-contact and high-speed, vision-based pose measurements have been widely used for aircraft performance testing in a wind tunnel. However, usually glass ports are used to protect cameras against the high-speed air?ow in?uence, which will lead to a big measurement error. In this paper, to further improve the vision-based pose measurement accuracy, an imaging model which considers the refraction light of the observation window was proposed. In this method, a nonlinear camera calibration model considering the refraction brought by the wind tunnel observation window, was established ?rst. What’s more, a new method for the linear calibration of the normal vector of the glass observation window was presented. Then, combining with the proposed matching method based on coplanarity constraint, the six pose parameters of the falling target could be calculated. Finally, the experimental setup was established to conduct the pose measurement study in the laboratory, and the results satis?ed the application requirements. Besides, experiments for verifying the vision measurement accuracy were also performed, and the results indicated that the displacement and angle measurement accuracy approximately increased by 57% and 33.6%, respectively, which showed the high accuracy of the proposed method.
关键词： pose parameters,machine vision,refraction,triangular vision,wind tunnel test
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) - Guangzhou, China (2018.10.8-2018.10.12)] 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) - Machine Vision-Based Segmentation and Classification Method for Intelligent Roller Surface Monitoring
摘要： The surface quality of steel rollers is a key factor determining the quality of final products such as metal sheets and foils in the rolling industry. It is important to examine the surface quality of rollers since rollers with optical defects will always duplicate the defects onto the metal sheet or foil during rolling. The typical optical defects of rollers after finish grinding include speckles, chatter marks, swirl marks and combination of all of the above. They can hardly be modeled or shaped by the approach of micro topography or SEM (scanning electrical microscope). In this paper, an on-site machine vision system is firstly applied for stable inspection for the optical defects on roller surfaces. Then, an improved optical defect segmentation algorithm is developed based on the active contour model and the images including chatter marks and swirl marks. The normal surface state is classified by the combination of methods of Gabor filters, KPCA method and ELM neural networks. Finally, experiment are carried out to verify the efficiency of the improved segmentation method and the recognition rate of the combined classification algorithm.
关键词： optical defect detection,big data,machine vision,roller surface monitoring
更新于2025-09-04 15:30:14