Camera Module Research Articles

A Wafer Level Packaged Fully Integrated Tunable Fabry-Pérot Filter With Extended Optical Range For Multispectral and Hyperspectral Imaging

We report on the design, fabrication and characterization of a wafer level packaged, vacuum sealed, fully integrated and cell-phone compatible tunable micromachined Fabry-Perot filter ( $\mu $ FPF), operating within the visual and near-infrared (VIS-NIR) optical range. Implementation of a normally closed architecture combined with the electrostatic actuation enlarging, rather than closing, the optical cavity allows to achieve enhanced tunability of the optical gap. To evaluate the design and operational parameters, an electro-opto-mechanical model of the device was built and the resulting system of equations, coupling the structural, squeeze film, electrostatic and electric circuit domains, was solved numerically. The devices with an optical aperture of 1.85 mm and with robust elastic suspensions made of single crystal Si were fabricated and, consistently with the model prediction, the filter tunability within the range between 100 nm and 500 nm was demonstrated in the experiments. Vertically integrated design resulted in a small, 1 mm, thickness of a fully assembled device. Due to its compact size, manufacturability and short response time within the millisecond range, our tunable filter can be directly integrated into mobile phone camera modules, portable hyperspectral imagers, and remote sensors.

Iot Based Emergency Security System for Women

In today’s era, women are progressing and scaling the peaks of success. However, there’s a significant hike in the number of crimes against women like molestation, eve-teasing, trafficking, etc. Also, there have been numerous attempts to ensure the safety of women ranging from the infamous mobile apps to the hefty belts &safety jackets,etc. However, it is not practical to carry such bulky systems and the victim may not be able to reach the smartphone without being noticed by the assaulter.This increases the risk factor. Therefore, to ensure the security of women, in this paper we propose an IOT based Emergency security system. This system includes a gsm, gps, raspberry pi, fingerprint module, camera module and IR led blasters. It aims at providing a dual security to the women with the help of panic button and fingerprint scanning device. Whenever a woman feels like she is in danger, she can manually switch on the system which will require her to scan her fingerprint for every 1 min. Practically, if she is in distress situation she would fail to scan and the camera module which is embedded in the woman’s pendant will start capturing images and live video. The GPS module will trace the exact location & GSM module will send emergency text messages to the specified contacts and alert the nearby police station. An additional provision of improved vision during night time using IR led blasters is incorporated in this system.

Automatic Headlight Beam Management System for Vehicles

Nowadays, most people driving vehicles tend to leave the high beam always on. Many people don’t realize how dangerous can be leaving the high beam on when an opposite vehicle approach. People find it tedious to control the high beam as they would have to turn on and off multiple times within a short span. This is where our algorithm comes into action. The Automatic Headlight Beam Management System for Vehicles automatically controls the vehicle’s beam and headlight with the predefined variable such as location, time, opposite vehicles approach. The Automatic Beam Management System for Vehicles employs modules such as camera, GPS, microcontroller to achieve the desired result. This system gathers live video recording from the camera modules and makes it greyscale with an intensity such that only the headlight will be visible. Then, colour inversion technique is applied to easily identify the opposite vehicle’s headlight. This confirms the approach of a vehicle. The method is employed in such a way that street lamps are not confused as vehicles. This data is then shared with a microcontroller which changes the beam.

Driver Distraction System using Face, Eye, Yawn And Pulse Detection

Secure car driving is an important entity for safety and is the first priority for any automobile driver and is the main reason for designing a system which captures the state of the drivers eyes and his/her facial variations combined with pulse fluctuations, altogether they gives us parameters to decide whether the driver should be notified or not. Eye detection - more precisely it analyses the eyes and check if they're closed or open using camera module the amount of frames during which eyes are closed is decided. When this number of frames is above a selected threshold, the drive will get a alert. Camera module periodically takes snaps so as to confirm safety..A true time system which captures the state of the driver which will benefit many of us round the globe.

FishCam: A low-cost open source autonomous camera for aquatic research.

We describe the "FishCam", a low-cost ( 500 USD) autonomous camera package to record videos and images underwater. The system is composed of easily accessible components and can be programmed to turn ON and OFF on customizable schedules. Its 8-megapixel camera module is capable of taking 3280×2464-pixel images and videos. An optional buzzer circuit inside the pressure housing allows synchronization of the video data from the FishCam with passive acoustic recorders. Ten FishCam deployments were performed along the east coast of Vancouver Island, British Columbia, Canada, from January to December 2019. Field tests demonstrate that the proposed system can record up to 212h of video data over a period of at least 14days. The FishCam data collected allowed us to identify fish species and observe species interactions and behaviors. The FishCam is an operational, easily-reproduced and inexpensive camera system that can help expand both the temporal and spatial coverage of underwater observations in ecological research. With its low cost and simple design, it has the potential to be integrated into educational and citizen science projects, and to facilitate learning the basics of electronics and programming.

Development of a Biomechatronic Device for Motion Analysis Through a RGB-D Camera

This work investigates the validity and reliability of a novel biomechatronic device providing an interactive environment in Augmented Reality (AR) for neuromotor rehabilitation. A RGB-depth camera and telemonitoring/remote signaling module are the main components of the device, together with a PC-based interface. The interactive environment, which implements some optimized algorithms of body motion capture and novel methodologies for human body motion analysis, enables neuromotor rehabilitation treatments that are adaptable to the performance and individual characteristics of the patient. The RGB-Depth camera module is implemented through a Microsoft Kinect, ORBBEC ZED2K devices; the telemonitoring module for teleassistance and therapy supervision is implemented as a cloud service.
 Within the module of body motion tracking, the abduction and adduction movements of the limbs of the full-body structure are tracked and the joints angles are measured in real-time; the most distinctive feature of the tracking module is the control of the trunk and shoulder posture during the exercises performed by the patient. Indeed, the device recognizes an incorrect position of the patient's body that could affect the objective of the exercise to be performed. The recognition of an incorrect exercise is associated to the generation of an alert both to the patient and the physician, in order to maximize the effectiveness of the treatment based on the user's potential and to increase the chances of a better biofeedback.
 The experimental tests, which have been carried out by reproducing several neuromotor exercises on the interactive environment, show that the feature recognition and extraction of the joints and segments of the musculo-skeletal structure of the patient's, and of wrong posture during exercises, can achieve good performance in the different experimental conditions. 
 The developed device is a valid tool for patients affected by chronic disability, but it could be extended to neurodegenerative diseases in the early stages of the disease. Thanks to the enhanced interactivity in augmented reality, the patient can overcome some difficulties in interaction with the most common IT tools and technologies; at the meanwhile she/he can perform rehabilitation at home. The physician can also check in real time the results and customize the care pathway.
 The enhanced interactivity provided by the device during rehabilitation session increases both the motivation by the patient and the continuity of the care, as well as it supports low-cost remote assistance and telemedicine by optimizing therapy costs.
 The key points are:
 
 i) making rehabilitation motivating for the patient, becoming a "player";
 ii) optimize effectiveness and costs;
 
 iii) possibility of low-cost remote assistance and telemedicine.

Design of a 5 degree of freedom–voice coil motor actuator for smartphone camera modules

Consumers pay most attention to the camera function of smartphones. Thus, manufacturers focus on improving the capabilities of camera modules to deliver clearer and sharper images to consumers. Today, camera modules with auto focusing (AF) and optical image stabilization (OIS) functions are standard in the industry. Specifically, OIS is of the linear movement and rotational movement types. In contrast to the rotational movement type, the commonly used linear movement type cannot compensate for rotational error. Therefore, this paper proposes a novel voice coil motor (VCM) actuator that can supply a 5 degree of freedom (DOF)–compensation that consists of three linear movements and two rotational movements for smartphone camera modules. This novel VCM actuator with 5-DOF compensation is realized using an innovative electromagnetic structure. This paper further verifies the properties of the proposed VCM actuator with a laboratory-built prototype. The experimental results verify the robust properties and feasibility of the proposed VCM actuator.

Image and WLAN Bimodal Integration for Indoor User Localization

Recently, we experience the increasing prevalence of wearable cameras, some of which feature Wireless Local Area Network (WLAN) connectivity, and the abundance of mobile devices equipped with on-board camera and WLAN modules. Motivated by this fact, this work presents an indoor localization system that leverages both imagery and WLAN data for enabling and supporting a wide variety of envisaged location-aware applications ranging from ambient and assisted living to indoor mobile gaming and retail analytics. The proposed solution integrates two complementary localization approaches, i.e., one based on WLAN and another one based on image location-dependent data, using a fusion engine. Two fusion strategies are developed and investigated to meet different requirements in terms of accuracy, run time, and power consumption. The one is a light-weight threshold-based approach that combines the location outputs of two localization algorithms, namely a WLAN-based algorithm that processes signal strength readings from the surrounding wireless infrastructure using an extended Naive Bayes approach and an image-based algorithm that follows a novel approach based on hierarchical vocabulary tree of SURF (Speeded Up Robust Features) descriptors. The second fusion strategy employs a particle filter algorithm that operates directly on the WLAN and image readings and also includes prior position estimation information in the localization process. Extensive experimental results using real-life data from an indoor office environment indicate that the proposed fusion strategies perform well and are competitive against standalone WLAN and imaged-based algorithms, as well as alternative fusion localization solutions.

Single Sensor Compressive Light Field Video Camera

AbstractThis paper presents a novel compressed sensing (CS) algorithm and camera design for light field video capture using a single sensor consumer camera module. Unlike microlens light field cameras which sacrifice spatial resolution to obtain angular information, our CS approach is designed for capturing light field videos with high angular, spatial, and temporal resolution. The compressive measurements required by CS are obtained using a random color‐coded mask placed between the sensor and aperture planes. The convolution of the incoming light rays from different angles with the mask results in a single image on the sensor; hence, achieving a significant reduction on the required bandwidth for capturing light field videos. We propose to change the random pattern on the spectral mask between each consecutive frame in a video sequence and extracting spatio‐angular‐spectral‐temporal 6D patches. Our CS reconstruction algorithm for light field videos recovers each frame while taking into account the neighboring frames to achieve significantly higher reconstruction quality with reduced temporal incoherencies, as compared with previous methods. Moreover, a thorough analysis of various sensing models for compressive light field video acquisition is conducted to highlight the advantages of our method. The results show a clear advantage of our method for monochrome sensors, as well as sensors with color filter arrays.

Rakshak An IoT Based Wearable Device for Women Safety

Women safety is a rising concern in many parts of the world. Crimes against women are increasing at an alarming rate. To counter this situation, a technology driven solution with the help of latest technological advancements can be developed. The aim is to develop an IoT based wearable device which works on the concept of voice recognition and allow women in the case of emergency. The device can send SOS messages to nearby help centers and relatives based on the person’s location when it is activated. The device can also collect evidence for further legal procedures and save them in a remote storage. The concepts of Internet of Things (IoT), Voice Recognition and Cloud Computing are used to achieve this. The objective is to use these concepts to develop a working prototype of a smart safety device for women that can help them in such situations and prevent such incidents from taking place. ‘Rakshak’ is an IOT based solution, which will help us to combat these situations effectively. It contains a concealed GSM, GPS, camera, microphone, and voice recognition module. The woman can activate a sequence of events using a voice command. The voice command will send out an SOS signal to contact list, and nearby authorities. The authorities can rush to the location of the incident and prevent it. The camera will start recording as soon as the voice command is activated, and this data will be sent to cloud storage. In case an attack takes place, the footage of this camera will serve as evidence against the attacker. In addition to preventing the incident, this device may create a sense of fear in their minds which may reduce the frequency of such incidents. Thus, this solution can be applicable as a wearable security device in different domains and can be used on a large scale to ensure women safety.

Energy Optimization and QoE Satisfaction for Wireless Visual Sensor Networks in Multi Target Tracking Scenario

Nowadays, by emerging new technologies, demand for a wireless visual sensor networks (WVSN) has been significantly increased. By providing the vital visual data from such networks, they play a substantial role in the surveillance applications. The wireless visual sensors (VSes) are the main component of these networks, which are equipped with camera and transceiver module. Energy optimization and satisfying the quality of the captured visual data, are two main contradictable issues in this area of research, especially in the target tracking applications. Therefore, these two issues have been simultaneously investigated in this paper. The coverage of the tracked targets and the quality of the captured visual data are considered as the quality of experienced (QoE). The desired threshold of QoE is defined by user. To optimize energy consumption with regard to QoE constraints in a multi target tracking scenario, an effective VSes selection is proposed. This method has been developed based on the convex optimization framework. Besides, the focal length of the VSes is set optimally by executing the proposed algorithm. Simulation results show efficiency of the proposed method compared with the optimal method (exhaustive search).

WIRELESS INFANT MONITORING SYSTEM BASED ON VIDEO OBJECT TRACKING AND ENVIRONMENTAL SENSORS

Many research has been going on for the development of better infant monitoring system to detect the cause of SIDs (Sudden Infant Deaths) among children and also to monitor or prevent infants from facing mechanical accidents or environmental discomfort. The proposed infant monitoring system is designed to detect the motion and the temperature of the infant using various IOT devices . A camera module is also used to capture videos which allows family members to monitor infant through videos. The data collected from all the sensors will be analyzed and hence will send an alert notification to the parents or relatives of the infant if found any abnormality in the measurements of the taken by the sensors . The technique also focuses on making the whole process of monitoring the infant portable. Which means users can easily monitor their kids from anywhere they want to without having their physical presence . KEYWORDS-IoT , Infant Monitoring System , Sensors, Cloud Computing

Single‐Layer Aberration‐Compensated Flat Lens for Robust Wide‐Angle Imaging

AbstractMetasurfaces are planarized and miniaturized versions of conventional optical elements. Subwavelength‐thick single‐layer metalenses have diffraction limited resolution for on‐axis imaging but relatively low resolution for off‐axis imaging due to off‐axial aberrations. The aberrations of planar single‐layer metalenses have been corrected by patterning two metasurfaces on both sides of a substrate to form metalens doublets with a thickness of hundreds of micrometers to millimeters. The multilevel diffractive lenses are demonstrated to achieve wide angle imaging with a thickness of several micrometers, however, the off‐axial aberrations are not compensated. Here, an epsilon‐greedy algorithm‐based scheme for achieving a planar wavelength‐thick single‐layer aberration‐compensated (SLAC) flat lens consisting of dielectric nanoring structures fabricated by 3D printing are proposed. The scheme is experimentally validated via a SLAC flat lens. This SLAC flat lens has a thickness of 1 µm, a numerical aperture of 0.45, a focal length of 1 mm, a full field of view (FOV) of 32° that enables aberration‐compensated imaging along the focal plane and monochromatic microscopic imaging with resolution better than 2.2 µm at a wavelength of 633 nm. This scheme can lead to ultrathin wide‐FOV flat lens designs as well as low‐cost mass production, which has various applications in miniscopes, mobile camera modules, and machine vision.

Low-cost multi-modal microscope using Raspberry Pi

This report describes a direction-dependent optical microscope operated with Raspberry Pi, with LED array illumination patterns controlled by Raspberry Pi. Images are obtained with a Raspberry Pi camera module. We demonstrate the use of Raspberry-Pi-based microscopes for multimodal imaging including bright-field microscopy, dark-field microscopy, differential phase-contrast microscopy, and polarization microscopy. We also demonstrate acquisition of direction-dependent dark-field and differential phase-contrast images. From a pair of opposite line or rectangular illumination, structures along the illumination axis were enhanced in dark-field images and differential phase-contrast images. Raspberry-Pi is open-source hardware. Raspberry-Pi-based compact, cost-effective, and multi-contrast microscopes are expected to be useful for science, technology, engineering and mathematics (STEM) education.

Flat-Field and Colour Correction for the Raspberry Pi Camera Module

The Raspberry Pi camera module is widely used in open source hardware projects as a low cost camera sensor. However, when the stock lens is removed and replaced with other custom optics the sensor will return a non-uniform background and colour response which hampers the use of this excellent and popular image sensor. This effect is found to be due to the sensor's optical design as well as due to built-in corrections in the GPU firmware, which is optimised for a short focal length lens. In this work we characterise and correct the vignetting and colour crosstalk found in the Raspberry Pi camera module v2, presenting two measures that greatly improve the quality of images using custom optics. First, we use a custom "lens shading table" to correct for vignetting of the image, which can be done in real time in the camera's existing processing pipeline (i.e. the camera's low-latency preview is corrected). The second correction is a colour unmixing matrix, which enables us to reverse the loss in saturation at the edge of the image, though this requires post-processing of the image. With both of these corrections in place, it is possible to obtain uniformly colour-corrected images, at the expense of slightly increased noise at the edges of the image.

Miniaturized 3D Depth Sensing-Based Smartphone Light Field Camera.

The miniaturization of 3D depth camera systems to reduce cost and power consumption is essential for their application in electrical devices that are trending toward smaller sizes (such as smartphones and unmanned aerial systems) and in other applications that cannot be realized via conventional approaches. Currently, equipment exists for a wide range of depth-sensing devices, including stereo vision, structured light, and time-of-flight. This paper reports on a miniaturized 3D depth camera based on a light field camera (LFC) configured with a single aperture and a micro-lens array (MLA). The single aperture and each micro-lens of the MLA serve as multi-camera systems for 3D surface imaging. To overcome the optical alignment challenge in the miniaturized LFC system, the MLA was designed to focus by attaching it to an image sensor. Theoretical analysis of the optical parameters was performed using optical simulation based on Monte Carlo ray tracing to find the valid optical parameters for miniaturized 3D camera systems. Moreover, we demonstrated multi-viewpoint image acquisition via a miniaturized 3D camera module integrated into a smartphone.

Post-operative monitoring of free flaps using a low-cost thermal camera: a pilot study

BackgroundCareful post-operative monitoring of free flaps is important in flap survival; immediate action increases flap salvage rate. Although various methods are available, room for improvement remains. Thermal cameras have proven their value in medicine and are nowadays readily available at low costs. The objective of this study was to evaluate the potential of an affordable infrared thermal camera and software in the detection of failing free flaps during post-operative monitoring.MethodsFree myocutaneous rectus abdominis flaps were harvested in 16 female landrace pigs and replanted after several hours of storage. All flaps were assessed with indocyanine green fluorescence angiography as well as hourly clinical assessment of skin colour, turgor and capillary refill. Furthermore, thermal photographs were taken simultaneously with the FLIR One thermal camera smartphone module. These photographs were processed in MATLAB and evaluated on their additional value as an indicator for flap failure.ResultsOut of 16 flaps, three flaps failed due to arterial failure and one flap developed venous congestion. The mean flap temperature compared to adjacent control skin proved to be most indicative for flap failure. All unsuccessful flaps showed lower temperatures after failure compared to the uncompromised free flaps.ConclusionsAn affordable thermal camera module can potentially contribute to post-operative free flap monitoring. Vascular compromise in free flaps can be distinguished by investigating relative temperature differences between the flap and reference skin. Until the FLIR One camera has been extensively investigated in a human population, it should be used in conjunction with conventional monitoring techniques.Level of evidence: Level IV, diagnostic study

Real Time Identification of Railway Track Surface Faults using Canny Edge Detector and 2D Discrete Wavelet Transform

Usually, railway accidents are caused by train derailment, the mechanical failure of tracks, such as broken rails often caused by lack of railway condition monitoring. Such monitoring could identify track surface faults, such as squats, that act as a catalyst for the track to crack and ultimately break. The research presented in this paper enables real-time identification of railway track faults using image processing techniques such as Canny edge detection and 2D discrete wavelet transformation. The Canny edge detection outperforms traditional track damage detection techniques including Axle Based Acceleration using Inertial Measurement Units and is as reliable as Fiber Bragg Grating. The Canny edge detection employed can identify squats in real-time owing to its specific threshold amplitude using a camera module mounted on a specially designed handheld Track Recording Vehicle (TRV). The 2D discrete wavelet transformation validates the insinuation of the Canny edge detector regarding track damage and furthermore determines damage severity, by applying high sub band frequency filter. The entire algorithm works on a Raspberry Pi 3 B+ utilizing an OpenCV API. When tested using an actual rail track, the algorithm proved reliable at determining track surface damage in real-time. Although wavelet transformation performs better than Canny edge detection in terms of determining the severity of track surface damage, it has processing overheads that become a bottleneck in real-time. To overcome this deficiency a very effective two-stage process has been developed.

The use of raspberry pi as a portable medical image processing

This paper presents the image processing implementation in Raspberry Pi. Raspberry Pi is a system built-in and is a low-cost computer that can be used to reduce system complexity in real-time applications. For programming, it’s very good to use Python. Raspberry pi has a Camera Slot Interface (CSI) to interface the camera with Raspberry Pi. Low contrast images captured using the Raspberry Pi camera module can be scaled up first to identify specific image regions. The most important processing is the removal of noise as a result of noise disturbance during image acquisition on the camera. Due to its small size, which is about the size of a credit card and its lightweight, raspberry pi is very suitable for use as a portable medical image processing system. Besides that Raspberry Pi also consumes low power.

Video Camera Data Display Unit

Video camera module are one of the most important components in designing and implementing image/video processing systems. Such kind of systems are widely used all over the world for a long period of time. Due to using in surveillance and guard, they have to have very small size. The aim of this article are following: present method for designing working prototype of a system, that displays data, that is transmitted from digital video camera module; solve the problems and issue, that shows up during projection. In the first chapter explains the reasons of creating video camera data display unit. In the second chapter you can see the process of choosing components, needed for creating prototype, such as microcontroller (STM32F429ZI) and video camera module (OV7670). This module provides visual information, captioned and transmitted to user interface. There are few interesting challenges about choosing OV7670 settings, like frame format and RGB coding. They were questioned and chosen in order to create working and functional prototype. In chapter three are listed detailed theoretical information about features of chosen video camera module, such as purpose of every contact from module, bits placement for RGB coding, and why that is so important in project. In the fourth chapter described block diagram of device, which is projected. Principle of work of projecting system also is given here. You can read there explaining the need for using such communication protocols as I2C, SPI and DCMI bus, that is used very often with video camera modules. Explained reasons of using DMA in the system and short instructions for configuring parameters of DMA. In chapter five described possibility of using different interfaces for transmitting output data to the user – such as Wi-Fi transmitting-receiving technology, based on TCP/IP protocol. It can help in improving projected system to an independent product, which can replicate full-fledged IP camera. Literary data analysis is carried out. It contains examples of similar systems and their detailed descriptions. Some of these details were used in creating both article and prototype. In conclusion, this article shows opportunities for hardware realization of video camera data display unit, based on OV7670 module and STM32F429ZI microcontroller. The features of connecting the video camera module, its synchronization and data transmission via the DCMI bus are considered. The parameters for data transmission, using DMA mode are defined. To visualize the video in the device prototype, was suggested LCD display, connected via the SPI bus. For full designed IP camera, it is necessary to add transceivers (like Wi-Fi) to the hardware and develop software to support the TCP / IP protocol, needed for embedded Web-server realization. Designed hardware and software of video camera data display unit gives a clear representation of all main steps, needed to implement this system.