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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (15 December 2017) | Viewed by 55388

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Special Issue Editor

Dr. Ivan Kotov

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Guest Editor

Brookhaven National Laboratory, Upton, NY 11973-5000, USA
Interests: Charge-Coupled Device (CCD) Sensors; CCD X-ray detectors; fully depleted CCD; EM CCD; CCD charge transfer efficiency; CCD test and characterization

Special Issue Information

Dear Colleagues,

Charge Coupled Devices (CCD) have revolutionized a broad range of fields, including astronomy, surveillance cameras, industrial cameras and scanners, motion detectors, and even created the new fields like digital photography. This technology has also paved the way for (complementary metal-oxide-semiconductor) CMOS sensors, including active pixel arrays (MAPS), and now they are taking the lead in fields where readout speed is crucially important.

This Special Issue aims to bring together recent research and developments concerning CCD and CMOS sensors.

Papers addressing developments in CCD and CMOS sensors are sought, including recent research and developments in sensors design, fabrication, characterization, and their applications. Both review articles and original research papers associated with CCD and CMOS sensors, and their applications, are solicited.

Dr. Ivan Kotov
Guest Editor

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Keywords

CCD
EM CCD
CMOS
MAPS
fully depleted CCD
CCD test and characterization
CCD design and fabrication

Published Papers (11 papers)

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Research

18 pages, 4582 KiB

Open AccessArticle

An Improved Electronic Image Motion Compensation (IMC) Method of Aerial Full-Frame-Type Area Array CCD Camera Based on the CCD Multiphase Structure and Hardware Implementation

by Hang Ren, Tao Tao Hu, Yu Long Song, Hui Sun, Bo Chao Liu and Ming He Gao

Sensors 2018, 18(8), 2632; https://doi.org/10.3390/s18082632 - 11 Aug 2018

Cited by 6 | Viewed by 4038

Abstract

In this paper, the performance of the electronic conventional image motion compensation (IMC) method based on the time delay integration (TDI) mode was analyzed using the optical injection formula of charge coupled devices (CCDs). The result shows that the non-synchronous effect of charge packet transfer caused by line-by-line transfer during exposure makes the compensated image dissatisfying. Then an improved electronic IMC method based on the CCD multiphase structure was proposed. In this method, a series of proper driving clocks were applied to drive the charge packet to move electrode-by-electrode during the exposure time, which results in a minimum non-synchronous effect of charge packet transfer. The mismatch of velocity between charge packet transfer and image motion was decreased. The performance of the improved electronic IMC method was also analyzed using the optical injection formula. The modulation degrees of the two methods were compared. The average value of the modulation degree of the improved electronic IMC method was 47/96, greater than the conventional electronic IMC method, which was 1/3. To achieve the improved electronic IMC, the driver timing diagram of the improved electronic IMC method was proposed. This paper presented an improved hardware implementation method for the improved electronic IMC method. Based on the basic FTF4052M drive circuit system, an IMC pulse pattern generator that worked together with the main pulse pattern generator (SAA8103) was added to achieve the improved electronic IMC. Then, the internal structure of the IMC pulse pattern generator was given. A dual pulse pattern generator drive circuit system was proposed. After computer simulation and indoor real shot verification, the compensation effect of the improved electronic IMC method was better than the compensation effect of the conventional electronic IMC method. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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21 pages, 5142 KiB

Open AccessArticle

Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net

by Jin Choi, Jung Hyun Jo, Hong-Suh Yim, Eun-Jung Choi, Sungki Cho and Jang-Hyun Park

Sensors 2018, 18(6), 1868; https://doi.org/10.3390/s18061868 - 7 Jun 2018

Cited by 10 | Viewed by 5490

Abstract

An Optical Wide-field patroL-Network (OWL-Net) has been developed for maintaining Korean low Earth orbit (LEO) satellites’ orbital ephemeris. The OWL-Net consists of five optical tracking stations. Brightness signals of reflected sunlight of the targets were detected by a charged coupled device (CCD). A chopper system was adopted for fast astrometric data sampling, maximum 50 Hz, within a short observation time. The astrometric accuracy of the optical observation data was validated with precise orbital ephemeris such as Consolidated Prediction File (CPF) data and precise orbit determination result with onboard Global Positioning System (GPS) data from the target satellite. In the optical observation simulation of the OWL-Net for 2017, an average observation span for a single arc of 11 LEO observation targets was about 5 min, while an average optical observation separation time was 5 h. We estimated the position and velocity with an atmospheric drag coefficient of LEO observation targets using a sequential-batch orbit estimation technique after multi-arc batch orbit estimation. Post-fit residuals for the multi-arc batch orbit estimation and sequential-batch orbit estimation were analyzed for the optical measurements and reference orbit (CPF and GPS data). The post-fit residuals with reference show few tens-of-meters errors for in-track direction for multi-arc batch and sequential-batch orbit estimation results. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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23 pages, 7010 KiB

Open AccessArticle

Experiments and Analysis of Close-Shot Identification of On-Branch Citrus Fruit with RealSense

by Jizhan Liu, Yan Yuan, Yao Zhou, Xinxin Zhu and Tabinda Naz Syed

Sensors 2018, 18(5), 1510; https://doi.org/10.3390/s18051510 - 11 May 2018

Cited by 19 | Viewed by 4413

Abstract

Fruit recognition based on depth information has been a hot topic due to its advantages. However, the present equipment and methods cannot meet the requirements of rapid and reliable recognition and location of fruits in close shot for robot harvesting. To solve this problem, we propose a recognition algorithm for citrus fruit based on RealSense. This method effectively utilizes depth-point cloud data in a close-shot range of 160 mm and different geometric features of the fruit and leaf to recognize fruits with a intersection curve cut by the depth-sphere. Experiments with close-shot recognition of six varieties of fruit under different conditions were carried out. The detection rates of little occlusion and adhesion were from 80–100%. However, severe occlusion and adhesion still have a great influence on the overall success rate of on-branch fruits recognition, the rate being 63.8%. The size of the fruit has a more noticeable impact on the success rate of detection. Moreover, due to close-shot near-infrared detection, there was no obvious difference in recognition between bright and dark conditions. The advantages of close-shot limited target detection with RealSense, fast foreground and background removal and the simplicity of the algorithm with high precision may contribute to high real-time vision-servo operations of harvesting robots. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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17 pages, 5686 KiB

Open AccessArticle

Green Grape Detection and Picking-Point Calculation in a Night-Time Natural Environment Using a Charge-Coupled Device (CCD) Vision Sensor with Artificial Illumination

by Juntao Xiong, Zhen Liu, Rui Lin, Rongbin Bu, Zhiliang He, Zhengang Yang and Cuixiao Liang

Sensors 2018, 18(4), 969; https://doi.org/10.3390/s18040969 - 25 Mar 2018

Cited by 38 | Viewed by 6191

Abstract

Night-time fruit-picking technology is important to picking robots. This paper proposes a method of night-time detection and picking-point positioning for green grape-picking robots to solve the difficult problem of green grape detection and picking in night-time conditions with artificial lighting systems. Taking a representative green grape named Centennial Seedless as the research object, daytime and night-time grape images were captured by a custom-designed visual system. Detection was conducted employing the following steps: (1) The RGB (red, green and blue). Color model was determined for night-time green grape detection through analysis of color features of grape images under daytime natural light and night-time artificial lighting. The R component of the RGB color model was rotated and the image resolution was compressed; (2) The improved Chan–Vese (C–V) level set model and morphological processing method were used to remove the background of the image, leaving out the grape fruit; (3) Based on the character of grape vertical suspension, combining the principle of the minimum circumscribed rectangle of fruit and the Hough straight line detection method, straight-line fitting for the fruit stem was conducted and the picking point was calculated using the stem with an angle of fitting line and vertical line less than 15°. The visual detection experiment results showed that the accuracy of grape fruit detection was 91.67% and the average running time of the proposed algorithm was 0.46 s. The picking-point calculation experiment results showed that the highest accuracy for the picking-point calculation was 92.5%, while the lowest was 80%. The results demonstrate that the proposed method of night-time green grape detection and picking-point calculation can provide technical support to the grape-picking robots. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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11 pages, 1119 KiB

Open AccessArticle

Analysis of Dark Current in BRITE Nanostellite CCD Sensors

by Adam Popowicz

Sensors 2018, 18(2), 479; https://doi.org/10.3390/s18020479 - 6 Feb 2018

Cited by 14 | Viewed by 4682

Abstract

The BRightest Target Explorer (BRITE) is the pioneering nanosatellite mission dedicated for photometric observations of the brightest stars in the sky. The BRITE charge coupled device (CCD) sensors are poorly shielded against extensive flux of energetic particles which constantly induce defects in the silicon lattice. In this paper we investigate the temporal evolution of the generation of the dark current in the BRITE CCDs over almost four years after launch. Utilizing several steps of image processing and employing normalization of the results, it was possible to obtain useful information about the progress of thermal activity in the sensors. The outcomes show a clear and consistent linear increase of induced damage despite the fact that only about 0.14% of CCD pixels were probed. By performing the analysis of temperature dependencies of the dark current, we identified the observed defects as phosphorus-vacancy (PV) pairs, which are common in proton irradiated CCD matrices. Moreover, the Meyer-Neldel empirical rule was confirmed in our dark current data, yielding

E_{M N} = 24.8

meV for proton-induced PV defects. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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20 pages, 7623 KiB

Open AccessArticle

Inclinometer Assembly Error Calibration and Horizontal Image Correction in Photoelectric Measurement Systems

by Xiaofang Kong, Qian Chen, Jiajie Wang, Guohua Gu, Pengcheng Wang, Weixian Qian, Kan Ren and Xiaotao Miao

Sensors 2018, 18(1), 248; https://doi.org/10.3390/s18010248 - 16 Jan 2018

Cited by 6 | Viewed by 3920

Abstract

Inclinometer assembly error is one of the key factors affecting the measurement accuracy of photoelectric measurement systems. In order to solve the problem of the lack of complete attitude information in the measurement system, this paper proposes a new inclinometer assembly error calibration and horizontal image correction method utilizing plumb lines in the scenario. Based on the principle that the plumb line in the scenario should be a vertical line on the image plane when the camera is placed horizontally in the photoelectric system, the direction cosine matrix between the geodetic coordinate system and the inclinometer coordinate system is calculated firstly by three-dimensional coordinate transformation. Then, the homography matrix required for horizontal image correction is obtained, along with the constraint equation satisfying the inclinometer-camera system requirements. Finally, the assembly error of the inclinometer is calibrated by the optimization function. Experimental results show that the inclinometer assembly error can be calibrated only by using the inclination angle information in conjunction with plumb lines in the scenario. Perturbation simulation and practical experiments using MATLAB indicate the feasibility of the proposed method. The inclined image can be horizontally corrected by the homography matrix obtained during the calculation of the inclinometer assembly error, as well. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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15 pages, 4774 KiB

Open AccessArticle

Research on Geometric Calibration of Spaceborne Linear Array Whiskbroom Camera

by Qinghong Sheng, Qi Wang, Hui Xiao and Qing Wang

Sensors 2018, 18(1), 247; https://doi.org/10.3390/s18010247 - 16 Jan 2018

Cited by 2 | Viewed by 4592

Abstract

The geometric calibration of a spaceborne thermal-infrared camera with a high spatial resolution and wide coverage can set benchmarks for providing an accurate geographical coordinate for the retrieval of land surface temperature. The practice of using linear array whiskbroom Charge-Coupled Device (CCD) arrays to image the Earth can help get thermal-infrared images of a large breadth with high spatial resolutions. Focusing on the whiskbroom characteristics of equal time intervals and unequal angles, the present study proposes a spaceborne linear-array-scanning imaging geometric model, whilst calibrating temporal system parameters and whiskbroom angle parameters. With the help of the YG-14—China’s first satellite equipped with thermal-infrared cameras of high spatial resolution—China’s Anyang Imaging and Taiyuan Imaging are used to conduct an experiment of geometric calibration and a verification test, respectively. Results have shown that the plane positioning accuracy without ground control points (GCPs) is better than 30 pixels and the plane positioning accuracy with GCPs is better than 1 pixel. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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15 pages, 6293 KiB

Open AccessArticle

Distance Calibration between Reference Plane and Screen in Direct Phase Measuring Deflectometry

by Shujun Huang, Yue Liu, Nan Gao, Zonghua Zhang, Feng Gao and Xiangqian Jiang

Sensors 2018, 18(1), 144; https://doi.org/10.3390/s18010144 - 6 Jan 2018

Cited by 15 | Viewed by 4678

Abstract

The recently developed direct phase measuring deflectometry (DPMD) method can directly measure the three-dimensional (3D) shape of specular objects with discontinuous surfaces, but requires a calibrated distance between a reference plane and liquid crystal display screen. Because the plane and screen are different distances from the imaging device, they cannot be clearly captured given the limited depth of field (DOF) of the lens. Therefore, existing machine vision-based methods cannot be used to effectively calibrate a DPMD system. In this paper, a new distance calibration method that uses a mirror with a hollow ring matrix pattern and a mobile stage is presented. The direction of the mobile stage in the camera coordinate system is determined by the mirror’s pattern at several positions in the camera’s DOF so that the reference position outside of the DOF can be calculated. The screen’s position can also be calibrated by displaying patterns at a known scale. Therefore, the required distance is accurately obtained in the camera coordinate system. Evaluation results show that the maximum value of the absolute error is less than 0.031 mm. The experimental results on an artificial stepped mirror and a reflected diamond distribution surface demonstrate the accuracy and practicality of the proposed method. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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2324 KiB

Open AccessArticle

High-Speed Focus Inspection System Using a Position-Sensitive Detector

by Binh Xuan Cao, Phuong Le Hoang, Sanghoon Ahn, Heeshin Kang, Jengo Kim and Jiwhan Noh

Sensors 2017, 17(12), 2842; https://doi.org/10.3390/s17122842 - 8 Dec 2017

Cited by 13 | Viewed by 5309

Abstract

Precise and rapid focus detection is an essential operation in several manufacturing processes employing high-intensity lasers. However, the detection resolution of existing methods is notably low. This paper proposes a technique that provides a rapid-response, high-precision, and high-resolution focus inspection system on the basis of geometrical optics and advanced optical instruments. An ultrafast interface position detector and a single-slit mask are used in the system to precisely signal the focus position with high resolution. The reflected images on the image sensor are of a high quality, and this quality is maintained persistently when the target surface is shifted along the optical axis. The proposed system developed for focus inspection is simple and inexpensive, and is appropriate for practical use in the industrial production of sophisticated structures such as microcircuits and microchips. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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5992 KiB

Open AccessArticle

A Denoising Method for Randomly Clustered Noise in ICCD Sensing Images Based on Hypergraph Cut and Down Sampling

by Meng Yang, Fei Wang, Yibin Wang and Nanning Zheng

Sensors 2017, 17(12), 2778; https://doi.org/10.3390/s17122778 - 30 Nov 2017

Cited by 6 | Viewed by 3990

Abstract

Intensified charge-coupled device (ICCD) images are captured by ICCD sensors in extremely low-light conditions. They often contains spatially clustered noises and general filtering methods do not work well. We find that the scale of the clustered noise in ICCD sensing images is often much smaller than that of the true structural information. Then the clustered noise can be identified by properly down-sampling and then up-sampling the ICCD sensing image and comparing it to the noisy image. Based on this finding, we present a denoising algorithm to remove the randomly clustered noise in ICCD images. First, we over-segment the ICCD image into a set of flat patches, and each patch contains very little structural information. Second, we classify the patches into noisy patches and noise-free patches based on the hypergraph cut method. Then the noise-free patches are easily recovered by the general block-matching and 3D filtering (BM3D) algorithm, since they often do not contain the clustered noise. The noisy patches are recovered by subtracting the identified clustered noise from the noisy patches. After that, we could get the whole recovered ICCD image. Finally, the quality of the recovered ICCD image is further improved by diminishing the remaining sparse noise with robust principal component analysis. Experiments are conducted on a set of ICCD images and compared with four existing denoising algorithms, which shows that the proposed algorithm removes well the randomly clustered noise and preserves the true textural information in the ICCD sensing images. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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17539 KiB

Open AccessArticle

Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras

by Chenglin Wang, Yunchao Tang, Xiangjun Zou, Lufeng Luo and Xiong Chen

Sensors 2017, 17(11), 2564; https://doi.org/10.3390/s17112564 - 7 Nov 2017

Cited by 46 | Viewed by 6276

Abstract

Recognition and matching of litchi fruits are critical steps for litchi harvesting robots to successfully grasp litchi. However, due to the randomness of litchi growth, such as clustered growth with uncertain number of fruits and random occlusion by leaves, branches and other fruits, the recognition and matching of the fruit become a challenge. Therefore, this study firstly defined mature litchi fruit as three clustered categories. Then an approach for recognition and matching of clustered mature litchi fruit was developed based on litchi color images acquired by binocular charge-coupled device (CCD) color cameras. The approach mainly included three steps: (1) calibration of binocular color cameras and litchi image acquisition; (2) segmentation of litchi fruits using four kinds of supervised classifiers, and recognition of the pre-defined categories of clustered litchi fruit using a pixel threshold method; and (3) matching the recognized clustered fruit using a geometric center-based matching method. The experimental results showed that the proposed recognition method could be robust against the influences of varying illumination and occlusion conditions, and precisely recognize clustered litchi fruit. In the tested 432 clustered litchi fruits, the highest and lowest average recognition rates were 94.17% and 92.00% under sunny back-lighting and partial occlusion, and sunny front-lighting and non-occlusion conditions, respectively. From 50 pairs of tested images, the highest and lowest matching success rates were 97.37% and 91.96% under sunny back-lighting and non-occlusion, and sunny front-lighting and partial occlusion conditions, respectively. Full article

(This article belongs to the Special Issue Charge-Coupled Device (CCD) Sensors)

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