Research on Fast Locating Solder Joint on Fully-Automatic LED Wire Bonder

2011 ◽  
Vol 105-107 ◽  
pp. 1827-1830
Author(s):  
Zhi Chao Huang ◽  
Mu Liu ◽  
Hua Dong Liu ◽  
Xing Ming Fan ◽  
Yi Zhong
Keyword(s):  
Solder Joint ◽  
Center Of Mass ◽  
Window Size ◽  
Adaptive Threshold ◽  
New Method ◽  
Median Filtering ◽  
Adaptive Window ◽  
Grey Scale ◽  
Fully Automatic ◽  
Potential Area

A new method is put forward to positioning solder joints on fully-automatic LED wire bonder. In the method, the image of a LED micro-chip is first processed with GPU by median filtering based on average and adaptive window size. Then the potential areas of the micro-chip are determined by the algorithm of adaptive threshold for image. These potential areas are stored in groups according to distances. The best potential area of each group is screened out in terms of symmetrical features of grey scale after that it is a weighted process. Finally, the LED micro-chip solder joint is precisely located by calculating the center of mass. The results show that the proposed method is fast, accurate, effective, suitable for automation, and has no requirement to the consistency of the shape of LED micro-chips.

Impulse Noise Suppression Method by Median Filtering with Parity Extraction

2013 ◽  
Vol 846-847 ◽  
pp. 991-994
Author(s):  
Zhen Xing Li
Keyword(s):  
Impulse Noise ◽  
Noise Suppression ◽  
Median Filter ◽  
Window Size ◽  
New Method ◽  
Median Filtering ◽  
Experiment Data ◽  
Simulation And Experiment ◽  
Suppression Method

A new impulse noise suppression method by median filtering with parity extraction was proposed in this paper. The window size of the median filter has important effect on the performance of the filtering result, larger window size can suppress impulse noise effectively but often at cost of loss of the detail information of the signal, while smaller window size can protect the detail information better but results in degrading of the noise suppression. Parity extraction is done to the signal at first and median filtering carries on the odd and even part respectively, and then a new method of median filtering with short window size to suppress the impulse noise is obtained. Simulation and experiment data of telemetry process results show the effectiveness of the proposed method.

Adaptive Median Filtering Based on Unsupervised Classification of Pixels

2013 ◽  
pp. 273-296 ◽  
Author(s):  
J. K. Mandal ◽  
Somnath Mukhopadhyay
Keyword(s):  
Clustering Algorithm ◽  
Digital Images ◽  
Unsupervised Classification ◽  
Median Filtering ◽  
Adaptive Window ◽  
Novel Approach ◽  
Weighted Median ◽  
Window Selection ◽  
Filtering Approach

This chapter deals with a novel approach which aims at detection and filtering of impulses in digital images through unsupervised classification of pixels. This approach coagulates directional weighted median filtering with unsupervised pixel classification based adaptive window selection toward detection and filtering of impulses in digital images. K-means based clustering algorithm has been utilized to detect the noisy pixels based adaptive window selection to restore the impulses. Adaptive median filtering approach has been proposed to obtain best possible restoration results. Results demonstrating the effectiveness of the proposed technique are provided for numeric intensity values described in terms of feature vectors. Various benchmark digital images are used to show the restoration results in terms of PSNR (dB) and visual effects which conform better restoration of images through proposed technique.

De-Noising of Binary Image Using Accelerated Local Median-Filtering Approach

2019 ◽  
pp. 164-185
Author(s):  
Amit Khan ◽  
Dipankar Majumdar
Keyword(s):  
Time Complexity ◽  
Window Size ◽  
Analytical Techniques ◽  
Approximate Solutions ◽  
Median Filtering ◽  
Binary Images ◽  
Noise Characteristics ◽  
Varied Size ◽  
Number Of Iterations ◽  
Filtering Approach

In the last few decades huge amounts and diversified work has been witnessed in the domain of de-noising of binary images through the evolution of the classical techniques. These principally include analytical techniques and approaches. Although the scheme was working well, the principal drawback of these classical and analytical techniques are that the information regarding the noise characteristics is essential beforehand. In addition to that, time complexity of analytical works amounts to beyond practical applicability. Consequently, most of the recent works are based on heuristic-based techniques conceding to approximate solutions rather than the best ones. In this chapter, the authors propose a solution using an iterative neural network that applies iterative spatial filtering technology with critically varied size of the computation window. With critical variation of the window size, the authors are able to show noted acceleration in the filtering approach (i.e., obtaining better quality filtration with lesser number of iterations).

Median filtering algorithm for adaptive window shape

2018 ◽  
Vol 26 (12) ◽  
pp. 3028-3039 ◽  
Author(s):  
邹永宁 ZOU Yong-ning ◽  
姚功杰 YAO Gong-jie
Keyword(s):  
Median Filtering ◽  
Filtering Algorithm ◽  
Adaptive Window

scholarly journals Algorithms for the Motion of Randomly Positioned Hexagonal and Square Microparts on a “Smart Platform” with Electrostatic Forces and a New Method for Their Simultaneous Centralization and Alignment

Micromachines ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 874
Author(s):  
Georgia Kritikou ◽  
Nikos Aspragathos ◽  
Vassilis Moulianitis
Keyword(s):  
Collision Avoidance ◽  
Center Of Mass ◽  
Initial Configuration ◽  
New Method ◽  
Electrostatic Forces ◽  
Multiple Electrodes ◽  
Parallel Motion ◽  
Glass Type

In this paper, an approach is proposed for the simultaneous manipulation of multiple hexagonal and square plastic–glass type microparts that are positioned randomly on a smart platform (SP) using electrostatic forces applied by the suitable activation of circular conductive electrodes. First, the statics analysis of a micropart on the SP is presented in detail and the forces and torques that are applied to and around the center of mass (COM) respectively due to the activation of a SP electrode are determined. The “single electrode activation” (SEA) and the “multiple electrodes activations” (MEA) algorithms are introduced to determine the feasible SP electrodes activations for the microparts manipulation considering their initial configuration. An algorithm for the simultaneous handling of multiple microparts is studied considering the collision avoidance with neighboring microparts. An approach is presented for the simultaneous centralization and alignment of the microparts preparing them for their batch parallel motion on the SP. The developed algorithms are applied to a simulated platform and the results are presented and discussed.

A New Method for Completely Force Balancing Simple Linkages

1969 ◽  
Vol 91 (1) ◽  
pp. 21-26 ◽  
Author(s):  
R. S. Berkof ◽  
G. G. Lowen
Keyword(s):  
Center Of Mass ◽  
Time Dependent ◽  
New Method ◽  
Practical Applications ◽  
Mass Distributions ◽  
Linearly Independent ◽  
Planar Linkages

A new method, herein referred to as the “Method of Linearly Independent Vectors,” is shown to permit the complete force balancing of certain planar linkages. This method consists of writing the equation describing the position of the total mechanism center of mass in such a way that the coefficients of the time-dependent terms may be set equal to zero. In this way, the total center of mass can be made stationary, and the shaking force vanishes. Derivations as well as practical applications are shown for four-bar and six-bar linkages with arbitrary link mass distributions.

ROBUST AND FAST TRACKING ALGORITHM IN VIDEO SEQUENCES BY ADAPTIVE WINDOW SIZING USING A NOVEL ANALYSIS ON SPATIOTEMPORAL GRADIENT POWERS

2007 ◽  
Vol 16 (02) ◽  
pp. 305-317 ◽  
Author(s):  
PAYMAN MOALLEM ◽  
ALIREZA MEMARMOGHADDAM ◽  
MOHSEN ASHOURIAN
Keyword(s):  
Window Size ◽  
Image Sequences ◽  
Tracking Algorithm ◽  
Video Sequences ◽  
Occupancy Rate ◽  
Tracking Method ◽  
Fast Tracking ◽  
Adaptive Window ◽  
Real Video ◽  
Adaptively Adjusting

Success of a tracking method depends largely on choosing the suitable window size as soon as the target size changes in image sequences. To achieve this goal, we propose a fast tracking algorithm based on adaptively adjusting tracking window. Firstly, tracking window is divided into four edge subwindows, and a background subwindow around it. Then, by calculating the spatiotemporal gradient power ratios of the target in each subwindow, four proper expansion vectors are associated with any tracking window sides such that the occupancy rate of the target in tracking window should be maintained within a specified range. In addition, since temporal changing of target is evaluated in calculating these vectors, we estimate overall target displacement by sum of expansion vectors. Experimental results using various real video sequences show that the proposed algorithm successfully track an unknown textured target in real time, and is robust to dynamic occlusions in complex noisy backgrounds.

Research on the High-Speed Object Shadowgraph Image Processing Method Based on Adaptive Threshold Segmentation

2013 ◽  
Vol 325-326 ◽  
pp. 1571-1575
Author(s):  
Fang Wang ◽  
Zong Wei Yang ◽  
De Ren Kong ◽  
Yun Fei Jia
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Center Of Mass ◽  
Image Data ◽  
Ccd Camera ◽  
Adaptive Threshold ◽  
Processing Method ◽  
Laser Source ◽  
Feature Points ◽  
Threshold Segmentation

Shadowgraph is an important method to obtain the flight characteristics of high-speed object, such as attitude and speed etc. To get the contour information of objects and coordinates of feature points from shadowgraph are the precondition of characteristics analysis. Current digital shadowgraph system composed of CCD camera and pulsed laser source is widely used, but still lack of the corresponding method in image processing. Therefore, the selection of an effective processing method in order to ensure high effectiveness and accuracy of image data interpretation is an urgent need to be solved. According to the features of shadowgraph, a processing method to realize the contour extraction of high-speed object by adaptive threshold segmentation is proposed based on median filtering in this paper, and verified with the OpenCV in VC environment, the identification process of the feature points are recognized. The result indicates that by using this method, contours of high-speed objects can be detected nicely, to combine relevant algorithm, the pixel coordinates of feature points such as the center of mass can be recognized accurately.

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