Process Monitoring in Automatic Assembly of Minilenses With Fiberscopes

2007 ◽  
Author(s):  
Tian Lan ◽  
Siying Chen ◽  
Guoqiang Ni
Keyword(s):  
Image Processing ◽  
Process Control ◽  
Process Monitoring ◽  
Optical Design ◽  
Experimental Results ◽  
Processing Unit ◽  
Automatic Assembly ◽  
Image Processing Algorithm ◽  
Step Size ◽  
Motion System

In this paper, we present experimental results of process monitoring and process control in automatic assembly of minilenses in front of a miniature flexible fiberscope. For the purpose of process visualization and process control, an LED light source, a grating and a micrometer screw are compacted together in a vacuum gripper. A positioning system, a fiber chuck, a mimilens magazine and a fiberscope have been installed in the system and an image processing algorithm for process control has been developed. The optical design and assembly process are presented here in details. The projection of an illuminated grating through the minilens on the fiberscope is used to position the minilens automatically by an image processing unit and the motion system. The position system has a minimum step size of 5 μm in translation and 0.01° by rotation. The repeatability of the translation stages is about ±2.5 μm. It is shown from the experimental results that the tilt axial angle between the optical axis of the minilens and the geometrical axis of the fiberscope is less than 4°.

scholarly journals AUTOMATIC MICROINJECTION SYSTEM USING STEREOSCOPIC MICROSCOPE

2014 ◽  
pp. 40-44
Author(s):  
Junko Sakiyama ◽  
Hideki Yamamoto
Keyword(s):  
Image Processing ◽  
Pattern Matching ◽  
Visual Feedback ◽  
Feedback System ◽  
Experimental Results ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Brain Areas ◽  
Reference Pattern ◽  
Tip Position

In this paper, we describe a visual feedback system using a stereoscopic microscope that controls a micromanipulator so that a needle head may pierce a target as much length as desired. At first, we developed an image processing algorithm for the tip of needle head to touch the target. Secondarily, we developed an algorithm for prediction of the tip position of the needle head within the target. By performing a preoperation, the shape of the needle head is preserved as a reference pattern. When the needle head piercing the target, the shape of the needle head within the target is predicted by pattern matching. Thus, we developed a microinjection system that axially pierces the target. Experimental results show that the proposed system may be useful in micromanipulation such as microinjection to brain areas in neuroanatomy.

scholarly journals Ambient Light Rejection Integrated Circuit for Autonomous Adaptation on a Sub-retinal Prosthetic System

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5638
Author(s):  
Hosung Kang ◽  
Hojong Choi ◽  
Jungsuk Kim
Keyword(s):  
Image Processing ◽  
Light Intensity ◽  
Image Sensor ◽  
Experimental Results ◽  
Image Processing Technique ◽  
Cmos Process ◽  
Processing Unit ◽  
Ambient Light ◽  
Retinal Implants ◽  
Autonomous Adaptation

This paper introduces an ambient light rejection (ALR) circuit for the autonomous adaptation of a subretinal implant system. The sub-retinal implants, located beneath a bipolar cell layer, are known to have a significant advantage in spatial resolution by integrating more than a thousand pixels, compared to epi-retinal implants. However, challenges remain regarding current dispersion in high-density retinal implants, and ambient light induces pixel saturation. Thus, the technical issues of ambient light associated with a conventional image processing technique, which lead to high power consumption and area occupation, are still unresolved. Thus, it is necessary to develop a novel image-processing unit to handle ambient light, considering constraints related to power and area. In this paper, we present an ALR circuit as an image-processing unit for sub-retinal implants. We first introduced an ALR algorithm to reduce the ambient light in conventional retinal implants; next, we implemented the ALR algorithm as an application-specific integrated chip (ASIC). The ALR circuit was fabricated using a standard 0.35-μm CMOS process along with an image-sensor-based stimulator, a sensor pixel, and digital blocks. As experimental results, the ALR circuit occupies an area of 190 µm2, consumes a power of 3.2 mW and shows a maximum response time of 1.6 sec at a light intensity of 20,000 lux. The proposed ALR circuit also has a pixel loss rate of 0.3%. The experimental results show that the ALR circuit leads to a sensor pixel (SP) being autonomously adjusted, depending on the light intensity.

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

A High Performance Image Processing Unit for On-orbit Servicing

2006 ◽  
Author(s):  
Hiroshi Yamamoto ◽  
Yasufumi Nagai ◽  
Shinichi Kimura ◽  
Hiroshi Takahashi ◽  
Satoko Mizumoto ◽  
...  
Keyword(s):  
Image Processing ◽  
High Performance ◽  
Processing Unit

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

Internal quality evaluation of chestnut using nuclear magnetic resonance

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Soo Hyun Park ◽  
Sang Ha Noh ◽  
Michael J. McCarthy ◽  
Seong Min Kim
Keyword(s):  
Image Processing ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Processing Algorithm ◽  
Internal Quality ◽  
Soluble Solid Content ◽  
Mr Images ◽  
Image Processing Algorithm ◽  
Internal Defects ◽  
Nuclear Magnetic

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

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