Rational Design of Activatable Lanthanide NIR-IIb Emissive Nanoprobe for In Situ Specific Imaging of HOCl In Vivo.

Hypochlorous acid (HOCl), as an indispensable signaling molecule in organisms, is one of the key members of reactive oxygen species (ROS). However, in vivo, real-time dynamic near-infrared fluorescence imaging of HOCl levels in the 1400-1700 nm sub-window (NIR-IIb) remains a major challenge due to the lack of suitable detection methods. Herein, a general design of HOCl-responsive NIR-IIb fluorescence nanoprobe is proposed by integrating NaLuF4Yb/Er@NaLuF4 downshift nanoparticles (DSNPs) and HOCl recognition/NIR-IIb emissive modulation unit of M2-xS (M = Cu, Co, Pb) nanodots for real-time monitoring of HOCl levels. The fluorescence modulation unit of M2-xS nanodots presents remarkably enhanced absorption than Yb sensitizer at 980 nm and greatly inhibits the NIR-IIb fluorescence emission via competitive absorption mechanism. While, the M2-xS nanodots are easily degraded after triggering by HOCl, resulting in HOCl responsive turn-on (≈ten folds) NIR-IIb emission at 1532 nm. More importantly, in vivo highly precise and specific monitoring of inflammatory with abnormal HOCl expression is successfully achieved. Thus, the explored competitive absorption mediated quenching-activation mechanism provides a new general strategy of designing HOCl-responsive NIR-IIb fluorescence nanoprobe for highly specific and sensitive HOCl detection.

Releaf: An Efficient Method for Real-Time Occlusion Handling by Game Theory.

Receiving uninterrupted videos from a scene with multiple cameras is a challenging task. One of the issues that significantly affects this task is called occlusion. In this paper, we propose an algorithm for occlusion handling in multi-camera systems. The proposed algorithm, which is called Real-time leader finder (Releaf), leverages mechanism design to assign leader and follower roles to each of the cameras in a multi-camera setup. We assign leader and follower roles to the cameras and lead the motion by the camera with the least occluded view using the Stackelberg equilibrium. The proposed approach is evaluated on our previously open-sourced tendon-driven 3D-printed robotic eye that tracks the face of a human subject. Experimental results demonstrate the superiority of the proposed algorithm over the Q-leaning and Deep Q Networks (DQN) baselines, achieving an improvement of 20% and 18% for horizontal errors and an enhancement of 81% for vertical errors, as measured by the root mean squared error metric. Furthermore, Releaf has the superiority of real-time performance, which removes the need for training and makes it a promising approach for occlusion handling in multi-camera systems.

Untethered Ultra-Wideband-Based Real-Time Locating System for Road-Worker Safety.

In order to reduce the accident risk in road construction and maintenance, this paper proposes a novel solution for road-worker safety based on an untethered real-time locating system (RTLS). This system tracks the location of workers in real time using ultra-wideband (UWB) technology and indicates if they are in a predefined danger zone or not, where the predefined safe zone is delimited by safety cones. Unlike previous works that focus on road-worker safety by detecting vehicles that enter into the working zone, our proposal solves the problem of distracted workers leaving the safe zone. This paper presents a simple-to-deploy safety system. Our UWB anchors do not need any cables for powering, synchronisation, or data transfer. The anchors are placed inside safety cones, which are already available in construction sites. Finally, there is no need to manually measure the positions of anchors and introduce them to the system thanks to a novel self-positioning approach. Our proposal, apart from automatically estimating the anchors' positions, also defines the limits of safe and danger zones. These features notably reduce the deployment time of the proposed safety system. Moreover, measurements show that all the proposed simplifications are obtained with an accuracy of 97%.

Real-Time Moving Object Tracking on Smartphone Using Cradle Head Servo Motor.

The increasing demand for artificially intelligent smartphone cradles has prompted the need for real-time moving object detection. Real-time moving object tracking requires the development of algorithms for instant tracking analysis without delays. In particular, developing a system for smartphones should consider different operating systems and software development environments. Issues in current real-time moving object tracking systems arise when small and large objects coexist, causing the algorithm to prioritize larger objects or struggle with consistent tracking across varying scales. Fast object motion further complicates accurate tracking and leads to potential errors and misidentification. To address these issues, we propose a deep learning-based real-time moving object tracking system which provides an accuracy priority mode and a speed priority mode. The accuracy priority mode achieves a balance between the high accuracy and speed required in the smartphone environment. The speed priority mode optimizes the speed of inference to track fast-moving objects. The accuracy priority mode incorporates CSPNet with ResNet to maintain high accuracy, whereas the speed priority mode simplifies the complexity of the convolutional layer while maintaining accuracy. In our experiments, we evaluated both modes in terms of accuracy and speed.

In-Operando Lithium-Ion Transport Tracking in an All-Solid-State Battery.

An all-solid-state battery is a secondary battery that is charged and discharged by the transport of lithium ions between positive and negative electrodes. To fully realize the significant benefits of this battery technology, for example, higher energy densities, faster charging times, and safer operation, it is essential to understand how lithium ions are transported and distributed in the battery during operation. However, as the third lightest element, methods for quantitatively analyzing lithium during operation of an all-solid-state device are limited such that real-time tracking of lithium transport has not yet been demonstrated. Here, the authors report that the transport of lithium ions in an all-solid-state battery is quantitatively tracked in near real time by utilizing a high-intensity thermal neutron source and lithium-6 as a tracer in a thermal neutron-induced nuclear reaction. Furthermore, the authors show that the lithium-ion migration mechanism and pathway through the solid electrolyte can be determined by in-operando tracking. From these results, the authors suggest that the development of all-solid-state batteries has entered a phase where further advances can be carried out while understanding the transport of lithium ions in the batteries.

Validation of an RF Image System for Real-Time Tracking Neurosurgical Tools.

A radio frequency (RF)-based system for surgical navigation is presented. Surgical navigation technologies are widely used nowadays for aiding the surgical team with many interventions. However, the currently available options still pose considerable limitations, such as line-of-sight occlusion prevention or restricted materials and equipment allowance. In this work, we suggest a different approach based on a microwave broadband antenna system. We combine techniques from microwave medical imaging, which can overcome the current limitations in surgical navigation technologies, and we propose methods to develop RF-based systems for real-time tracking neurosurgical tools. The design of the RF system to perform the measurements is shown and discussed, and two methods (Multiply and Sum and Delay Multiply and Sum) for building the medical images are analyzed. From these measurements, a surgical tool's position tracking system is developed and experimentally assessed in an emulated surgical scenario. The reported results are coherent with other approaches found in the literature, while overcoming their main practical limitations. The discussion of the results discloses some hints on the validity of the system, the optimal configurations depending on the requirements, and the possibilities for future enhancements.

Effectiveness of Artificial Neural Networks for Solving Inverse Problems in Magnetic Field-Based Localization.

Recently, indoor localization has become an active area of research. Although there are various approaches to indoor localization, methods that utilize artificially generated magnetic fields from a target device are considered to be the best in terms of localization accuracy under non-line-of-sight conditions. In magnetic field-based localization, the target position must be calculated based on the magnetic field information detected by multiple sensors. The calculation process is equivalent to solving a nonlinear inverse problem. Recently, a machine-learning approach has been proposed to solve the inverse problem. Reportedly, adopting the k-nearest neighbor algorithm (k-NN) enabled the machine-learning approach to achieve fairly good performance in terms of both localization accuracy and computational speed. Moreover, it has been suggested that the localization accuracy can be further improved by adopting artificial neural networks (ANNs) instead of k-NN. However, the effectiveness of ANNs has not yet been demonstrated. In this study, we thoroughly investigated the effectiveness of ANNs for solving the inverse problem of magnetic field-based localization in comparison with k-NN. We demonstrate that despite taking longer to train, ANNs are superior to k-NN in terms of localization accuracy. The k-NN is still valid for predicting fairly accurate target positions within limited training times.

Surgical Navigation System for Hypertensive Intracerebral Hemorrhage Based on Mixed Reality.

Hypertensive intracerebral hemorrhage (HICH) is an intracerebral bleeding disease that affects 2.5 per 10,000 people worldwide each year. An effective way to cure this disease is puncture through the dura with a brain puncture drill and tube; the accuracy of the insertion determines the quality of the surgery. In recent decades, surgical navigation systems have been widely used to improve the accuracy of surgery and minimize risks. Augmented reality- and mixed reality-based surgical navigation is a promising new technology for surgical navigation in the clinic, aiming to improve the safety and accuracy of the operation. In this study, we present a novel multimodel mixed reality navigation system for HICH surgery in which medical images and virtual anatomical structures can be aligned intraoperatively with the actual structures of the patient in a head-mounted device and adjusted when the patient moves in real time while under local anesthesia; this approach can help the surgeon intuitively perform intraoperative navigation. A novel registration method is used to register the holographic space and serves as an intraoperative optical tracker, and a method for calibrating the HICH surgical tools is used to track the tools in real time. The results of phantom experiments revealed a mean registration error of 1.03 mm and an average time consumption of 12.9 min. In clinical usage, the registration error was 1.94 mm, and the time consumption was 14.2 min, showing that this system is sufficiently accurate and effective for clinical application.

Applications of cognitive internet of medical things in modern healthcare.

The sudden outbreak of the novel coronavirus disease in 2019, known as COVID-19 has impacted the entire globe and has forced governments of various countries to a partial or full lockdown in the fear of the rapid spread of this disease. The major lesson learned from this pandemic is that there is a need to implement a robust system by using non-pharmaceutical interventions for the prevention and control of new contagious viruses. This goal can be achieved using the platform of the Internet of Things (IoT) because of its seamless connectivity and ubiquitous sensing ability. This technology-enabled healthcare sector is helpful to monitor COVID-19 patients properly by adopting an interconnected network. IoT is useful for improving patient satisfaction by reducing the rate of readmission in the hospital. The presented work discusses the applications and technologies of IoT like smart and wearable devices, drones, and robots which are used in healthcare systems to tackle the Coronavirus pandemic This paper focuses on applications of cognitive radio-based IoT for medical applications, which is referred to as "Cognitive Internet of Medical Things" (CIoMT). CIoMT is a disruptive and promising technology for dynamic monitoring, tracking, rapid diagnosis, and control of pandemics and to stop the spread of the virus. This paper explores the role of the CIoMT in the health domain, especially during pandemics, and also discusses the associated challenges and research directions.

Tracking Hepatic Ischemia-Reperfusion Injury in Real Time with a Reversible NIR-IIb Fluorescent Redox Probe.

Hepatic ischemia-reperfusion injury (HIRI) is responsible for liver dysfunction, which involves reactive oxygen species (ROS) as the most critical marker. Real-time monitoring of ROS during HIRI can provide significant chance for early diagnosis and timely intervention. However, there is no probe available to track ROS fluctuations during HIRI in vivo, as it is extremely challenging to design reversibly responsive fluorescent probe in near-infrared region. Here, a reversible redox probe REPOMs emitting beyond 1500 nm is proposed to fill the blank, using rare earth ions-doped nanoparticles as emitter, and molybdenum-based polyoxometalate nanoclusters as the ROS-recognition site and emission modulator. REPOMs exhibited excellent response towards the repeated cycle between ROS and glutathione, based on which the time-resolved ROS changes during HIRI were successfully obtained. This reversible probe may provide a powerful tool to promote the hepatology research in the future.

Real-time device tracking under MRI using an acousto-optic active marker.

PURPOSE: This work aims to demonstrate the use of an "active" acousto-optic marker with enhanced visibility and reduced radiofrequency (RF) -induced heating for interventional MRI. METHODS: The acousto-optic marker was fabricated using bulk piezoelectric crystal and π-phase shifted fiber Bragg grating (FBGs) and coupled to a distal receiver coil on an 8F catheter. The received MR signal is transmitted over an optical fiber to mitigate RF-induced heating. A photodetector converts the optical signal into electrical signal, which is used as the input signal to the MRI receiver plug. Acousto-optic markers were characterized in phantom studies. RF-induced heating risk was evaluated according to ASTM 2182 standard. In vivo real-time tracking capability was tested in an animal model under a 0.55T scanner. RESULTS: Signal-to-noise ratio (SNR) levels suitable for real-time tracking were obtained by using high sensitivity FBG and piezoelectric transducer with resonance matched to Larmor frequency. Single and multiple marker coils integrated to 8F catheters were readout for position and orientation tracking by a single acousto-optic sensor. RF-induced heating was significantly reduced compared to a coax cable connected reference marker. Real-time distal tip tracking of an active device was demonstrated in an animal model with a standard real-time cardiac MR sequence. CONCLUSION: Acousto-optic markers provide sufficient SNR with a simple structure for real-time device tracking. RF-induced heating is significantly reduced compared to conventional active markers. Also, multiple RF receiver coils connected on an acousto-optic modulator can be used on a single catheter for determining catheter orientation and shape.

BIFNOM: Binary-Coded Features on Normal Maps.

We propose a novel method for detecting features on normal maps and describing binary features, called BIFNOM, which is three-dimensionally rotation invariant and detects and matches interest points at high speed regardless of whether a target is textured or textureless and rigid or non-rigid. Conventional methods of detecting features on normal maps can also be applied to textureless targets, in contrast with features on luminance images; however, they cannot deal with three-dimensional rotation between each pair of corresponding interest points due to the definition of orientation, or they have difficulty achieving fast detection and matching due to a heavy-weight descriptor. We addressed these issues by introducing a three dimensional local coordinate system and converting a normal vector to a binary code, and achieved more than 750fps real-time feature detection and matching. Furthermore, we present an extended descriptor and criteria for real-time tracking, and evaluate the performance with both simulation and actual system.

Duration-dependent margins for prostate radiotherapy-a practical motion mitigation strategy.

BACKGROUND AND OBJECTIVE: The magnitude of intra-fractional prostate displacement (change from initial position over time) is associated with the duration of the patient lying on the radiotherapy treatment couch. This study reports a minute-by-minute association and calculates the impact of this displacement on duration-dependent margins using real-time intra-fractional position data monitored by four-dimensional transperineal ultrasound (4D TPUS). MATERIALS AND METHODS: A total of 55 patients were recruited prospectively. Intra-fractional position of the prostate was monitored in real-time using a 4D TPUS Clarity® system. A total of 1745 monitoring sessions were analysed. Van Herk's margin recipe (2.5∑ + 1.64((σ2 + σp2)1/2 - σp)) was used to estimate the duration-dependant margins for every minute, up to the 15th minute. Linear regression analysis was then performed on the overall margins against time and direction. RESULTS: The mean intra-fractional position was 0.76 mm Inferior (Inf), 0 mm Lateral (Lat) and 0.94 mm Posterior (Post) at the 15th minute. A minimum margin expansion of 2.42 mm (Superior/Inf), 1.02 mm (Left/Right) and 2.65 mm (Anterior/Post) was required for an 8­minute treatment compared to 4.29 mm (Sup/Inf), 1.84 mm (Lt/Rt) and 4.63 mm (Ant/Post) for a 15-minute treatment. The required margin expansion increased linearly (R2 = 0.99) in all directions (p < 0.01). However, while there was no statistically significant difference (p = 0.10) in the required margin expansion in the Sup/Inf and Ant/Post directions respective of the time duration, the margins were much bigger compared to those in the Lt/Rt direction (p < 0.01). CONCLUSION: We report our experience in deriving the minimum duration-dependant margin to generate the required planning target volume for prostate radiotherapy. The required margin increases linearly in all directions within the 15-min duration; thus, the margin will depend on the duration of the technique chosen (IMRT/VMAT/3DCRT/proton).

Continuous real time 3D motion reproduction using dynamic MRI and precomputed 4DCT deformation fields.

Radiotherapy of mobile tumors requires specific imaging tools and models to reduce the impact of motion on the treatment. Online continuous nonionizing imaging has become possible with the recent development of magnetic resonance imaging devices combined with linear accelerators. This opens the way to new guided treatment methods based on the real-time tracking of anatomical motion. In such devices, 2D fast MR-images are well-suited to capture and predict the real-time motion of the tumor. To be used effectively in an adaptive radiotherapy, these MR images have to be combined with X-ray images such as CT, which are necessary to compute the irradiation dose deposition. We therefore developed a method combining both image modalities to track the motion on MR images and reproduce the tracked motion on a sequence of 3DCT images in real-time. It uses manually placed navigators to track organ interfaces in the image, making it possible to select anatomical object borders that are visible on both MRI and CT modalities and giving the operator precise control of the motion tracking quality. Precomputed deformation fields extracted from the 4DCT acquired in the planning phase are then used to deform existing 3DCT images to match the tracked object position, creating a new set of 3DCT images encompassing irregularities in the breathing pattern for the complete duration of the MRI acquisition. The final continuous reconstructed 4DCT image sequence reproduces the motion captured by the MRI sequence with high precision (difference below 2 mm).

Wearable Hand Module and Real-Time Tracking Algorithms for Measuring Finger Joint Angles of Different Hand Sizes with High Accuracy using FBG Strain Sensor.

This paper presents a wearable hand module which was made of five fiber Bragg grating (FBG) strain sensor and algorithms to achieve high accuracy even when worn on different hand sizes of users. For real-time calculation with high accuracy, FBG strain sensors move continuously according to the size of the hand and the bending of the joint. Representatively, four algorithms were proposed; point strain (PTS), area summation (AREA), proportional summation (PS), and PS/interference (PS/I or PS/I_α). For more accurate and efficient assessments, 3D printed hand replica with different finger sizes was adopted and quantitative evaluations were performed for index~little fingers (77 to 117 mm) and thumb (68~78 mm). For index~little fingers, the optimized algorithms were PS and PS/I_α. For thumb, the optimized algorithms were PS/I_α and AREA. The average error angle of the wearable hand module was observed to be 0.47 ± 2.51° and mean absolute error (MAE) was achieved at 1.63 ± 1.97°. These results showed that more accurate hand modules than other glove modules applied to different hand sizes can be manufactured using FBG strain sensors which move continuously and algorithms for tracking this movable FBG sensors.

Real-Time Optoacoustic Tracking of Single Moving Micro-objects in Deep Phantom and Ex Vivo Tissues.

Medical imaging plays an important role in diagnosis and treatment of multiple diseases. It is a field which seeks for improved sensitivity and spatiotemporal resolution to allow the dynamic monitoring of diverse biological processes that occur at the micro- and nanoscale. Emerging technologies for targeted diagnosis and therapy such as nanotherapeutics, microimplants, catheters, and small medical tools also need to be precisely located and monitored while performing their function inside the human body. In this work, we show for the first time the real-time tracking of moving single micro-objects below centimeter thick phantom tissue and ex vivo chicken breast, using multispectral optoacoustic tomography (MSOT). This technique combines the advantages of ultrasound imaging regarding depth and resolution with the molecular specificity of optical methods, thereby facilitating the discrimination between the spectral signatures of the micro-objects from those of intrinsic tissue molecules. The resulting MSOT signal is further improved in terms of contrast and specificity by coating the micro-objects' surface with gold nanorods, possessing a unique absorption spectrum, which facilitate their discrimination from surrounding biological tissues when translated to future in vivo settings.

Multiple-Color Platinum Complex with Super-Large Stokes Shift for Super-Resolution Imaging of Autolysosome Escape.

It is of great significance to track the platinum drugs in real time with super-resolution to elucidate their mechanism of action, such as their behavior and distribution in live cells. Such information is required for further drug development. However, it is always challenging to design platinum complexes suitable for such research. Herein, we design a luminescent building block (L) for metal complexes and a dinuclear platinum complex (Pt2 L) for super-resolution imaging. Because of its super-large Stokes shift and excellent photophysical properties, Pt2 L is capable of serving as an ideal candidate for super-resolution imaging with extremely low luminescence background and high photobleaching resistance. Moreover, upon light stimulation, a matter flux of Pt2 L escaping from autolysosomes to nucleus was observed, which represents a new transportation path. Utilizing the photoactivated escape properties, we can regulate the nuclear accessibility of Pt2 L form autolysosomes with photo-selectivity, which provides a new way to improve the targeting of platinum drugs.

Augmented reality for dental implantology: a pilot clinical report of two cases.

BACKGROUND: Despite the limited number of articles dedicated to its use, augmented reality (AR) is an emerging technology that has shown to have increasing applications in multiple different medical sectors. These include, but are not limited to, the Maxillo-facial and Dentistry disciplines of medicine. In these medical specialties, the focus of AR technology is to achieve a more visible surgical field during an operation. Currently, this goal is brought about by an accurate display of either static or dynamic diagnostic images via the use of a visor or specific glasses. The objective of this study is to evaluate the feasibility of using a virtual display for dynamic navigation via AR. The secondary outcome is to evaluate if the use of this technology could affect the accuracy of dynamic navigation. CASE PRESENTATION: Two patients, both needing implant rehabilitation in the upper premolar area, were treated with flapless surgery. Prior to the procedure itself, the position of the implant was virtually planned and placed for each of the patients using their previous scans. This placement preparation contributed to a dynamic navigation system that was displayed on AR glasses. This, in turn, allowed for the use of a computer-aided/image-guided procedure to occur. Dedicated software for surface superimposition was then used to match the planned position of the implant and the real one obtained from the postoperative scan. Accuracies, using this procedure were evaluated by way of measuring the deviation between real and planned positions of the implants. For both surgeries it was possible to proceed using the AR technology as planned. The deviations for the first implant were 0.53 mm at the entry point and 0.50 mm at the apical point and for the second implant were 0.46 mm at the entry point and 0.48 mm at the apical point. The angular deviations were respectively 3.05° and 2.19°. CONCLUSIONS: From the results of this pilot study, it seems that AR can be useful in dental implantology for displaying dynamic navigation systems. While this technology did not seem to noticeably affect the accuracy of the procedure, specific software applications should further optimize the results.

Dynamic navigation: a prospective clinical trial to evaluate the accuracy of implant placement.

AIM: The objective of this prospective pilot clinical study was to evaluate the accuracy of a new dynamic navigation system and postoperative clinical outcomes. MATERIALS AND METHODS: Ten patients were recruited and 18 implants were placed. The surgery was performed with the navigation system and according to the virtual planning. Ten implants were placed using a flapless technique and eight implant sites were prepared with a combined piezo-drill method. The deviation between the real implant position obtained from the postoperative cone beam computed tomography (CBCT) scan and the planned implant position was measured. RESULT: The average deviation was 1.19 ± 0.54 mm. The mean deviation measured at the insertion point was 1.04 ± 0.47 mm and at the apical point it was 1.35 ± 0.56 mm. The depth error was 0.43 ± 0.34 mm. The axis deviation was 6.46 ± 3.95 degrees. No significant differences were found between the flapless and the open-flap approaches and between the conventional and piezoelectric techniques. No complications occurred. CONCLUSION: The accuracy values reported in this study are comparable, although not superior, to the literature data regarding dynamic and static computer-guided surgery. Dynamic navigation could increase the quality and safety of interventions and may reduce morbidity when compared with freehand insertion techniques. Deviation at the entry point (mm) Deviation at the apex (mm) Depth deviation (mm) Angular deviation (degrees) Mean 1.04 1.35 0.43 6.46 SD 0.47 0.56 0.34 3.95 Maximum 2.21 2.28 1.41 6.46 Minimum 0.45 0.59 0.03 3.95 Deviation at the entry point (mm)Deviation at the apex (mm)Depth deviation (mm)Angular deviation (degrees)OF0.96 ± 0.331.45 ± 0.600.35 ± 0.227.93 ± 5.15FL1.10 ± 0.581.27 ± 0.570.49 ± 0.425.28 ± 2.60Data are shown as mean ± SDOF = open-flap surgery; FL = flapless surgery Deviation at the entry point (mm)Deviation at the apex (mm)Depth deviation (mm)Angular deviation (degrees)P1.01 ± 0.251.37 ± 0.480.44 ± 0.267.63 ± 4.30C1.06 ± 0.621.34 ± 0.660.42 ± 0.415.52 ± 3.81Data are shown as mean ± SDP = piezoelectric tips; C = conventional burs.

Improved Target Signal Source Tracking and Extraction Method Based on Outdoor Visible Light Communication Using a Cam-Shift Algorithm and Kalman Filter.

An improved Cam-Shift algorithm with a Kalman filter applied to image-sensor based on outdoor visible light communication (OVLC) is presented in this paper. The proposed optimized tracking algorithm is used to track and extract the region of the target signal source Light Emitting Diode (LED) that carries modulated information for data transmission. Extracting the target signal source LED area is the premise of an image-sensor-based VLC system, especially in outdoor dynamic scenes. However, most of the existing VLC studies focus on data transmission rate, visible light positioning, etc. While the actual first step of realizing communication is usually ignored in the field of VLC, especially when the transmitter (signal source LED) or the receiver (image sensor) is moving in a more complex outdoor environment. Therefore, an improved tracking algorithm is proposed in this paper, aiming at solving the problem of extracting the region of the target signal source LED accurately in dynamic scenes with different interferences so as to promote the feasibility of VLC applications in outdoor scenes. The proposed algorithm considers color characteristics and special distribution characteristics of the moving target at the same time. The image is converted to a color probability distribution map based on the color histogram of the target and adaptively adjusts the location and size of the search window based on the results obtained from the previous frame. Meanwhile, it predicts the motion state of the target in the next frame according to the position and velocity information of the current frame to enhance accuracy and robustness of tracking. Experimental results show that the tracking error of the proposed algorithm is 0.85 cm and the computational time of processing one frame is 0.042 s. Besides, results also show that the improved algorithm can track and extract the target signal source LED area completely and accurately in an environment of many interference factors. This study confirms that the proposed algorithm can be applied to an OVLC system with many interferences to realize the actual first step of communication in an image-sensor-based VLC system, laying foundations for subsequent data transmission and other steps.