Adjustment of vision system parameters and image processing algorithms for measurement of miniature parts in automatic assembly

2011 ◽  
Author(s):  
Wang Xiaodong ◽  
ChenYong ◽  
Luo Yi ◽  
Chen Liang ◽  
Ma Tianming ◽  
...  
Keyword(s):  
Image Processing ◽  
Vision System ◽  
Automatic Assembly ◽  
System Parameters ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Image synthesis methodology for algorithm testing and vision system design

2002 ◽  
Vol 216 (5) ◽  
pp. 669-682 ◽  
Author(s):  
J M Parker ◽  
K-M Lee
Keyword(s):  
Image Processing ◽  
System Design ◽  
Vision System ◽  
Image Synthesis ◽  
Image Understanding ◽  
Design Parameters ◽  
Wide Range ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Synthesis Methodology

Although it is well-recognized and widely accepted that vision adds considerable flexibility, and it has also been shown that numerical simulation can aid in image understanding and vision system design (significantly reducing the engineering time to design and implement such systems), the utilization of image synthesis as an aid in algorithm and system design still remains a largely underexplored area. In machine vision applications, accuracy of the image generally outweighs image appearance. Unfortunately, the focus of most commercially available simulation methods is on photorealistic image synthesis; this is insufficient to design vision systems or evaluate and compare image-processing algorithms for part-presentation tasks: physically accurate, rather than photo-realistic, synthesis methods are necessary to sufficiently simulate captured image grey-scale values. This paper presents a methodology to generate physically accurate synthetic images efficiently in order to provide an accurate, flexible and practical means of evaluating the performance of image-processing algorithms for numerous hardware/software configuration combinations and a wide range of parts. While the synthesis methodology cannot fully compensate for the real environment, it can be used efficiently to study the effects of vision system design parameters on image accuracy. This provides an insight into the efficacy of the design and the ability of suggested image-processing algorithms to perform adequately for specific applications; furthermore, it may provide a means for correcting apparent errors in image-processing results.

Classification of Defects on Semiconductor Wafers Using Priority Rules

2004 ◽  
Vol 230-232 ◽  
pp. 135-148 ◽  
Author(s):  
N.G. Shankar ◽  
Z.W. Zhong ◽  
N. Ravi
Keyword(s):  
Image Processing ◽  
Defect Structure ◽  
Vision System ◽  
Semiconductor Industry ◽  
Priority Rules ◽  
Semiconductor Wafer ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Wafer Surfaces

This paper presents a template-based vision system to detect and classify the nonuniformaties that appear on the semiconductor wafer surfaces. Design goals include detection of flaws and correlation of defect features based on semiconductor industry expert’s knowledge. The die pattern is generated and kept as the reference beforehand from the experts in the semiconductor industry. The system is capable of identifying the defects on the wafers after die sawing. Each unique defect structure is defined as an object. Objects are grouped into user-defined categories such as chipping, metallization peel off, silicon dust contamination, etc., after die sawing and micro-crack, scratch, ink dot being washed off, bridging, etc., from the wafer. This paper also describes the vision system in terms of its hardware modules, as well as the image processing algorithms utilized to perform the functions.

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.

Elastic Graph-based Semi-supervised Embedding with Adaptive Loss Regression

2020 ◽  
Keyword(s):  
Image Processing ◽  
International Symposium ◽  
Fast Track ◽  
Electronic Imaging ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Fast track article for IS&T International Symposium on Electronic Imaging 2020: Image Processing: Algorithms and Systems proceedings.

scholarly journals Fractional-Order Colour Image Processing

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 457
Author(s):  
Manuel Henriques ◽  
Duarte Valério ◽  
Paulo Gordo ◽  
Rui Melicio
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Fractional Derivative ◽  
Fractional Order ◽  
Fractional Derivatives ◽  
Grey Scale ◽  
Colour Image ◽  
Colour Image Processing ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Many image processing algorithms make use of derivatives. In such cases, fractional derivatives allow an extra degree of freedom, which can be used to obtain better results in applications such as edge detection. Published literature concentrates on grey-scale images; in this paper, algorithms of six fractional detectors for colour images are implemented, and their performance is illustrated. The algorithms are: Canny, Sobel, Roberts, Laplacian of Gaussian, CRONE, and fractional derivative.

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