Search

This paper presents a biomimetic, lightweight, 3D printed and customizable robotic hand with locking mechanism consisting of Twisted and Coiled Polymer (TCP) muscles based on nylon precursor fibers as artificial muscles. Previously, we have presented a small-sized biomimetic hand using nylon based artificial muscles and fishing line muscles as actuators. The current study focuses on an adult-sized prosthetic hand with improved design and a position/force locking system. Energy efficiency is always a matter of concern to make compact, lightweight, durable and cost effective devices. In natural human hand, if we keep holding objects for long time, we get tired because of continuous use of energy for keeping the fingers in certain positions. Similarly, in prosthetic hands we also need to provide energy continuously to artificial muscles to hold the object for a certain period of time, which is certainly not energy efficient. In this work we, describe the design of the robotic hand and locking mechanism along with the experimental results on the performance of the locking mechanism.

Ground penetrating radar (GPR) has the ability to detect buried targets with little or no metal content. Achieving superior detection performance with a hand-held GPR can be very challenging due to the quality of the data, inconsistency of target signatures, variety of target types, and effects of a human operator. In this paper, we investigate the use of a local binary patterns (LBP) feature vector for target versus non-target discrimination from hand-held GPR data. First, a prescreener algorithm is applied to the GPR data. Then, a GPR B-scan is gathered at each prescreener alarm location and separated into several spatial and depth regions. LBP processing is applied to each spatial and depth cell individually and the LBP features from each cell are group together to form a feature vector. The resulting LBP features are invariant to amplitude scaling and represent the texture in the data. Using this feature vector, a classifier is trained to perform target versus non-target discrimination at each prescreener declaration. Experimental results illustrate the ability of the LBP features to improve detection of buried targets, especially low-metal and non-metal anti-tank and anti-personnel targets.

Pathological tremor results in undesired motion of body parts, with the greatest effect typically occurring in the hands. Since common treatment methods are ineffective in some patients or have risks associated with surgery or side effects, researchers are investigating mechanical means of tremor suppression. This work explores the viability of dielectric elastomers as the actuators in a tremor suppression control system. Dielectric elastomers have many properties similar to human muscle, making them a natural fit for integration into the human biomechanical system. This investigation develops a model of the integrated wrist-actuator system to determine actuator parameters that produce the necessary control authority without significantly affecting voluntary motion. Furthermore, this paper develops a control law for the actuator voltage to increase the effective viscous damping of the system. Simulations show excellent theoretical tremor suppression, demonstrating the potential for dielectric elastomers to suppress tremor while maximizing compatibility between the actuator and the human body.

The availability of hand held lasers, commonly termed “laser pointers” is easy and wide spread, through commercial web sites and brick & mortar stores. The output of these hand held devices ranges from 1-5 milliWatts (mW) the legal laser pointer output limit, to 5000mW (5Watts). This is thousand times the maximum limit for pointers. Sadly the abuse of these devices is also wide spread. Over the last few years over 3000 aircraft are exposed to laser hits per year. While these aircraft exposures are of no danger to the aircraft frame but they can cause pilot distractions with the potential to cause a serve accident. The presentation will discuss the problem review visual effects, the regulatory response and how educators need to be aware of the problem and can take steps to educate students in the hope of having an effect.

The identification of hand postures based on force myography (FMG) measurements using a fiber specklegram sensor is reported. The microbending transducers were attached to the user forearm in order to detect the radial forces due to hand movements, and the normalized intensity inner products of output specklegrams were computed with reference to calibration positions. The correlation between measured specklegrams and postures was carried out by artificial neural networks, resulting in an overall accuracy of 91.3% on the retrieval of hand configuration.

Hand vein image has been widely used in biological recognition, auxiliary medical and other fields. People with age, height, weight, gender differences have distinction in fat thickness of the back of hand, so the contrast and sharpness of their hand vein images are different too, which may affect the results of applications. In this paper, a hand vein image acquisition system is given and the hand vein images of people from the age of 3 to 60 are obtained in various conditions. The effect on the images caused by ages, genders, BMI (body mass index) and FMI (fat mass index) are researched and the statistical characteristics of the images are analyzed. The types of applicable people are also proposed for applications.

Three-dimensional hand-held optoacoustic imaging comes with important advantages that prompt the clinical translation of this modality, with applications envisioned in cardiovascular and peripheral vascular disease, disorders of the lymphatic system, breast cancer, arthritis or inflammation. Of particular importance is the multispectral acquisition of data by exciting the tissue at several wavelengths, which enables functional imaging applications. However, multispectral imaging of entire three-dimensional regions is significantly challenged by motion artefacts in concurrent acquisitions at different wavelengths. A method based on acquisition of volumetric datasets having a microsecond-level delay between pulses at different wavelengths is described in this work. This method can avoid image artefacts imposed by a scanning velocity greater than 2 m/s, thus, does not only facilitate imaging influenced by respiratory, cardiac or other intrinsic fast movements in living tissues, but can achieve artifact-free imaging in the presence of more significant motion, e.g., abrupt displacements during handheld-mode operation in a clinical environment.

Automatic and precise segmentation of hand bones is important for many medical imaging applications. Although several previous studies address bone segmentation, automatically segmenting articulated hand bones remains a challenging task. The highly articulated nature of hand bones limits the effectiveness of atlas-based segmentation methods. The use of low-level information derived from the image-of-interest alone is insufficient for detecting bones and distinguishing boundaries of different bones that are in close proximity to each other. In this study, we propose a method that combines an articulated statistical shape model and a local exemplar-based appearance model for automatically segmenting hand bones in CT. Our approach is to perform a hierarchical articulated shape deformation that is driven by a set of local exemplar-based appearance models. Specifically, for each point in the shape model, the local appearance model is described by a set of profiles of low-level image features along the normal of the shape. During segmentation, each point in the shape model is deformed to a new point whose image features are closest to the appearance model. The shape model is also constrained by an articulation model described by a set of pre-determined landmarks on the finger joints. In this way, the deformation is robust to sporadic false bony edges and is able to fit fingers with large articulations. We validated our method on 23 CT scans and we have a segmentation success rate of ~89.70 %. This result indicates that our method is viable for automatic segmentation of articulated hand bones in conventional CT.

In this paper, a method of recognition of multi-modal biometrics for palmprint and hand vein based on the feature layer fusion is proposed, combined with the characteristics of an improved canonical correlation analysis (CCA) and two dimensional principal component analysis (2DPCA). After pretreatment respectively, feature vectors of palmprint and hand vein images are extracted using two dimensional principal component analysis (2DPCA)，then fused in the feature level using the improved canonical correlation analysis(CCA), so identification can be done by a adjacent classifier finally. Using this method, two biometric information can be fused and the redundancy of information between features can effectively eliminated, the problem of the high-dimensional and small sample size can be overcome too. Simulation experimental results show that the proposed method in this paper can effectively improve the recognition rate of identification.

This paper presents a natural representation of numerical digit(s) using hand activity analysis based on number of fingers out stretched for each numerical digit in sequence extracted from a video. The analysis is based on determining a set of six features from a hand image. The most important features used from each frame in a video are the first fingertip from top, palm-line, palm-center, valley points between the fingers exists above the palm-line. Using this work user can convey any number of numerical digits using right or left or both the hands naturally in a video. Each numerical digit ranges from 0 to9. Hands (right/left/both) used to convey digits can be recognized accurately using the valley points and with this recognition whether the user is a right / left handed person in practice can be analyzed. In this work, first the hand(s) and face parts are detected by using YCbCr color space and face part is removed by using ellipse based method. Then, the hand(s) are analyzed to recognize the activity that represents a series of numerical digits in a video. This work uses pixel continuity algorithm using 2D coordinate geometry system and does not use regular use of calculus, contours, convex hull and datasets.

A novel artistic virtual reality (VR) environment was developed and tested for use as a rehabilitation protocol for post-stroke hand rehabilitation therapy. The system was developed by an interdisciplinary team of engineers, art therapists, occupational therapists, and VR artists to improve patients' motivation and engagement. Specific exercises were developed to explicitly promote the practice of therapeutic tasks requiring hand and arm coordination for upper extremity rehabilitation. Here we describe system design, development, and user testing for efficiency, subject's satisfaction and clinical feasibility. We report results of the completed qualitative, pre-clinical pilot study of the system effectiveness for therapy. Fourteen stroke survivors with chronic hemiparesis participated in a single training session within the environment to gauge user response to the protocol through a custom survey. Results indicate that users found the system comfortable, enjoyable, tiring; instructions clear, and reported a high level of satisfaction with the VR environment and rehabilitation task variety and difficulty. Most patients reported very positive impressions of the VR environment and rated it highly, appreciating its engagement and motivation. We are currently conducting a longitudinal intervention study over 6 weeks in stroke survivors with chronic hemiparesis. Initial results following use of the system on the first subjects demonstrate that the system is operational and can facilitate therapy for post stroke patients with upper extremity impairment.

In this work, an integrated contactless multiple hand feature acquisition system is designed. The system can capture palmprint, palm vein, and palm dorsal vein images simultaneously. Moreover, the images are captured in a contactless manner, that is, users need not to touch any part of the device when capturing. Palmprint is imaged under visible illumination while palm vein and palm dorsal vein are imaged under near infrared (NIR) illumination. The capturing is controlled by computer and the whole process is less than 1 second, which is sufficient for online biometric systems. Based on this device, this paper also implements a contactless hand-based multimodal biometric system. Palmprint, palm vein, palm dorsal vein, finger vein, and hand geometry features are extracted from the captured images. After similarity measure, the matching scores are fused using weighted sum fusion rule. Experimental results show that although the verification accuracy of each uni-modality is not as high as that of state-of-the-art, the fusion result is superior to most of the existing hand-based biometric systems. This result indicates that the proposed device is competent in the application of contactless multimodal hand-based biometrics.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Vein recognition is becoming an effective method for personal recognition. Vein patterns lie under the skin surface of human body, and hence provide higher reliability than other biometric traits and hard to be damaged or faked. This paper proposes a novel vein feature representation method call orientation of local binary pattern (OLBP) which is an extension of local binary pattern (LBP). OLBP can represent the orientation information of the vein pixel which is an important characteristic of vein patterns. Moreover, the OLBP can also indicate on which side of the vein centerline the pixel locates. The OLBP feature maps are encoded by 4-bit binary values and an orientation distance is developed for efficient feature matching. Based on OLBP feature representation, we construct a hand vein recognition system employing multiple hand vein patterns include palm vein, dorsal vein, and three finger veins (index, middle, and ring finger). The experimental results on a large database demonstrate the effectiveness of the proposed approach.

A prototype neurosurgical hand-held optical coherence tomography (OCT) imaging probe has been developed to provide micron resolution cross-sectional images of subsurface tissue during open surgery. This new ergonomic hand-held probe has been designed based on our group's previous work on electrostatically driven optical fibers. It has been packaged into a catheter probe in the familiar form factor of the clinically accepted Bayonet shaped neurosurgical non-imaging Doppler ultrasound probes. The optical design was optimized using ZEMAX simulation. Optical properties of the probe were tested to yield an ~20 um spot size, 5 mm working distance and a 3.5 mm field of view. The scan frequency can be increased or decreased by changing the applied voltage. Typically a scan frequency of less than 60Hz is chosen to keep the applied voltage to less than 2000V. The axial resolution of the probe was ~15 um (in air) as determined by the OCT system. A custom-triggering methodology has been developed to provide continuous stable imaging, which is crucial for clinical utility. Feasibility of this probe, in combination with a 1310 nm swept source OCT system was tested and images are presented to highlight the usefulness of such a forward viewing handheld OCT imaging probe. Knowledge gained from this research will lay the foundation for developing new OCT technologies for endovascular management of cerebral aneurysms and transsphenoidal neuroendoscopic treatment of pituitary tumors.

A Gen-2 hand-held optical imager has been developed capable of 2D surface imaging and 3D tomography. In the current work, the capability of the imager to resolve two closely placed targets is assessed via 2D and 3D tomographic studies. Resolution studies have been carried out under various experimental conditions using slab phantoms. Preliminary 2D surface images of reflected measurements have demonstrated the ability of the system to resolve 0.95cm diameter targets placed 0.5cm apart at 2cm depth. Three dimensional tomography reconstructions are currently performed to assess the resolution capacity under different experimental conditions.

A novel Gen-2 hand-held optical imager was developed with capabilities to contour to different tissue curvatures, perform simultaneous illumination and detection and imager large tissue surfaces. Experimental studies using cubical phantoms demonstrated that the imager can detect targets up to 2.5 cm and 5 cm deep via reflectance and transmission measurements, respectively. The target was also localized as regions of high absorption during multi-scan imaging of curved breast phantoms via both reflectance and transmission modes. Preliminary in-vivo breast imaging demonstrated that the target can be detected via varying the pressure applied during imaging, as observed from reflectance-based imaging studies on healthy adults with superficially placed target(s) in the intra-mammary fold.

We propose a mobile robot control method using 3D hand pose estimation without using sensors or controllers. The hand pose estimation we propose reduces the number of image features per data set, which makes the construction of a large-scale database possible, as well as estimation of the 3D hand poses of unspecified users with individual differences without sacrificing estimation accuracy. The system involves the construction in advance of a large database comprising three elements: hand joint information including the wrist, low-order proportional information on the hand images indicating the rough hand shape, and hand pose data comprised of low-order image features per data set.

Biometric identification is an important guarantee for social security. In recent years, as the development of social and economic, the more accuracy and safety of identification are required. The person identity verification systems that use a single biometric appear inherent limitations in accuracy, user acceptance, universality. Limitations of unimodal biometric systems can be overcome by using multimodal biometric systems, which combines the conclusions made by a number of unrelated biometrics indicators. Aiming at the limitations of unimodal biometric identification, a recognition algorithm for multimodal biometric fusion based on hand vein, iris and fingerprint was proposed. To verify person identity, the hand vein images, iris images and fingerprint images were preprocessed firstly. The region of interest (ROI) of hand vein image was obtained and filtered to reduce image noises. The multiresolution analysis theory was utilized to extract the texture information of hand vein. The iris image was preprocessed through iris localization, eyelid detection, image normalization and image enhancement, and then the feature code of iris was extracted from the detail images obtained using wavelet transform. The texture feature information represented fingerprint pattern was extracted after filtering and image enhancement. The Bayesian theorem was employed to realize the fusion at the matching score level and the fusion recognition result was finally obtained. The experimental results were presented, which showed that the recognition performance of the proposed fusion method was obviously higher than that of single biometric recognition algorithm. It had verified the efficiency of the proposed method for biometrics.

Several hand-held based optical imaging devices have been developed towards breast imaging, which are portable, patient-comfortable, and use non-ionizing radiation. The devices developed to date are limited in that they have flat probe faces and are incapable of real-time coregistration (as needed for 3-D tomographic imaging). A hand-held based optical imager has been developed in our lab, which has unique features of (i) simultaneous over sequential source illumination, which enables rapid data acquisition, (ii) a flexible probe face, which enables it to contour to any tissue curvature, and (iii) self coregistration facilities towards 3-D tomographic imaging. Real-time coregistration is demonstrated using the imager via fluorescence-enhanced studies in the continuous-wave mode, performed on slab phantoms (filled with 1% Liposyn solution) and in vitro samples (chicken breast). Additionally, preliminary studies were conducted using curved phantoms. In all cases, a 0.45-cc target filled with 1 μM Indocyanine green was used to represent a tumor. Real-time 2-D surface images of the phantom were obtained via multiple scans at different target depths. Preliminary surface imaging studies demonstrated that the summation of multiple scans distinctly differentiated the target from artifacts (up to 3 cm deep), which was not possible from individual scans.

To assess vascular responses of the human hand to inspiratory gasps and hand cooling, two imaging "remote sensing" instruments were utilized: 1) a high-resolution infrared (IR) imaging camera and 2) a full-field laser perfusion imager (FLPI). Data analysis was performed on the data sets collected simultaneously from both instruments. A non-localized drop of both FLPI and IR signals was observed at ~0.5-2.0 min after gasp onset. Spontaneous oscillations, much below the human cardiac and respiratory frequencies, were observed with both imagers. The dominant oscillations for both imaging modalities centered around 0.01Hz. Spectral frequencies, their power, and the duration of temperature oscillations (bursts) for different hand areas changed in time and were spatially heterogeneous. The highest spatial correlation between the two data sets was found between the mean IR derivative image and the mean original FLPI image for the baseline conditions. Heterogeneous images of the human hand were consistently detected non-invasively by both instruments. After cooling, a temperature elevation of ~0.5oC was seen as a spotted pattern mainly in the thenar and hypothenar areas. A generalized increase in perfusion over the same areas was observed in FLPI images. Both IR and FLPI imagers sensitively identify vasoconstrictor responses induced by inspiratory gasp and hand cooling maneuvers. The specificity to physiological changes and high imaging rate for both instruments, coupled with the current ease of use of optical cameras in clinical settings, make the described combination of two instruments an ideal imaging approach to studying the dynamics of thermal and perfusion heterogeneity in human skin.

Hand-held based optical imagers have become a new research interest for its maximum patient comfort, less bulky instrument and potential for clinical translation towards breast cancer diagnostics. However, its ability for optical tomography is either limited by depth recovery since only reflectance measurements were obtained using a hand-held design for imaging. In this study, we introduced a self-guided multi-projection technique, which can take advantage of potential portability of hand-held probe based system, towards improvement of target depth recovery during fluorescence optical tomography studies.

A mobile hand held battery powered sensor based on fringe projection technique for preservation of fossil traces and archaeological excavations was developed. It consists of a projector and two cameras and covers a measuring field of about 240 mm x 175 mm x 160 mm. The core time for data acquisition is 0.34 s and the final result of a 3D point cloud is obtained in less than five seconds. Errors due to movements of the sensor are detected and can be swept out. The sensor allows the capturing of 3D data of the observed surface together with colour information. It was successfully applied at fossil find of traces of a dinosaur at rock layers from Triassic. 3D reconstruction of a part of the excavation was realized including the determination of the depth of traces.

Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

Tracking moving objects is an area increasingly known in computer vision field. It plays a very important role in human-computer interaction. In this context we have developed a hand tracking and gesture recognition system that allows interaction with the machine in an intuitive and natural way. To ensure the tracking we apply the Kalman filter and detect the optimal points of the hand in order to determine the gesture expressed by user.

A tablet computer with a depth camera and a color camera is loaded on a traditional shopping cart. The inside information of the shopping cart is obtained by two cameras. In the shopping cart monitoring field, it is very important for us to determine whether the customer with goods in or out of the shopping cart. This paper establishes a basic framework for judging empty hand, it includes the hand extraction process based on the depth information, process of skin color model building based on WPCA (Weighted Principal Component Analysis), an algorithm for judging handheld products based on motion and skin color information, statistical process. Through this framework, the first step can ensure the integrity of the hand information, and effectively avoids the influence of sleeve and other debris, the second step can accurately extract skin color and eliminate the similar color interference, light has little effect on its results, it has the advantages of fast computation speed and high efficiency, and the third step has the advantage of greatly reducing the noise interference and improving the accuracy.

This paper describes progressive generations of hand held triangulation sensors for measuring small features, from edge breaks to corrosion pits. We describe the design considerations, ergonomics, packaging and interface between the device and part, such as the sensor tip and optional fixtures. We then present a customized design to address different types of surface features and defects. Next, we present the calibration concept, and its execution. The paper closes by summarizing system performance evaluation experiments and their results. It was shown that the system is capable of measuring edges down to a radius of 250 microns at a repeatability of 50 microns.

Hand-based authentication is a key biometric technology with a wide range of potential applications both in industry and government. Traditionally, hand-based authentication is performed by extracting information from the whole hand. To account for hand and finger motion, guidance pegs are employed to fix the position and orientation of the hand. In this paper, we consider a component-based approach to hand-based verification. Our objective is to investigate the discrimination power of different parts of the hand in order to develop a simpler, faster, and possibly more accurate and robust verification system. Specifically, we propose a new approach which decomposes the hand in different regions, corresponding to the fingers and the back of the palm, and performs verification using information from certain parts of the hand only. Our approach operates on 2D images acquired by placing the hand on a flat lighting table. Using a part-based representation of the hand allows the system to compensate for hand and finger motion without using any guidance pegs. To decompose the hand in different regions, we use a robust methodology based on morphological operators which does not require detecting any landmark points on the hand. To capture the geometry of the back of the palm and the fingers in suffcient detail, we employ high-order Zernike moments which are computed using an effcient methodology. The proposed approach has been evaluated on a database of 100 subjects with 10 images per subject, illustrating promising performance. Comparisons with related approaches using the whole hand for verification illustrate the superiority of the proposed approach. Moreover, qualitative comparisons with state-of-the-art approaches indicate that the proposed approach has comparable or better performance.

Bioluminescent photoproteins, such as aequorin and obelin, are proteins that emit light upon binding calcium. Aequorin and obelin contain four EF-hand domains arranged into a globular structure. The loop region of these EF-hand domains binds calcium by coordinating it in a pentagonal bipyramidal structure with oxygen atoms. The binding of calcium to these EF-hands causes a slight conformational change in the protein, which leads to the oxidation of the internally sequestered chromophore, coelenterazine, producing coelenteramide and CO 2 . The excited coelenteramide then relaxes radiatively, emitting bioluminescence at 471 nm in aequorin or 491 nm in obelin. Although calcium is the traditional, and generally the most powerful, triggering ligand in this bioluminescence reaction, alternative di- and trivalent cations can also bind to the EF-hand loops and stimulate luminescence. Species capable of this cross-reactivity include: Cd 2+ , Ba 2+ , Mn 2+ , Sr 2+ , Mg 2+ , and several lanthanides. Magnesium is also known to modulate the bioluminescence of wild-type aequorin, increase its stability, and decrease its aggregation tendency. Both wild-type aequorin and wild-type obelin contain several cysteine residues, aequorin has three and obelin has five. It is believed that these cysteine residues play an important, but as of yet unknown, role in the bioluminescence of these proteins, since mutating most of these residues causes significant loss in bioluminescent activity. In order to explore whether or not these cysteine residues contributed to the specificity of the EF-hand domains for cations we generated four aequorin and obelin mutants and observed their luminescent intensity and decay kinetics by stimulation with calcium, barium, and magnesium. It was found that the cysteine mutations do appear to alter the effects that alternative divalent cations have on the bioluminescence of both aequorin and obelin.

A new approach to classifying the hand geometry features for personal verification is presented. This paper attempts to improve the performance of hand geometry-based systems by applying the Support Vector Machine (SVM) to the template classification task. We also compare the SVM-based approach to vector distance-based and neural network-based approaches as well as to other systems described in the literature and to the popular commercial systems. The testing results show that our system is competitive to the other known solutions.© (2006) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Different hand-derived biometric traits have been used for user authentication in many commercial systems. In this paper we have investigated the possibility of using a new biometric trait, the knuckle, for user authentication. Knuckle regions are extracted from the hand images and correlation methods are used for the purpose of verification. Experimental results on a data set of 125 people show that the knuckle is a viable biometric trait, which can be used as an alternative to finger and palm prints or in conjunction with them.

Prostate biopsy is the clinical standard for the definitive diagnosis of prostate cancer. To overcome the limitations of 2D TRUS-guided biopsy systems when targeting pre-planned locations, systems have been developed with 3D guidance to improve the accuracy of cancer detection. Prostate deformation due to needle insertion and biopsy gun firing is a potential source of error that can cause target misalignments during biopsies. We use non-rigid registration of 2D TRUS images to quantify the deformation during the needle insertion and the biopsy gun firing procedure, and compare this effect in biopsies performed using a handheld TRUS probe with those performed using a mechanically assisted 3D TRUS guided biopsy system. Although the mechanically assisted biopsy system had a mean deformation approximately 0.2 mm greater than that of the handheld approach, it yielded a lower relative increase of deformation near the needle axis during the needle insertion stage and greater deformational stability of the prostate during the biopsy gun firing stage. We also analyzed the axial and lateral components of the tissue motion; our results indicated that the motion is weakly biased in the direction orthogonal to the needle, which is less than ideal from a targeting standpoint given the long, narrow cylindrical shape of the biopsy core.

Since 2002, our research group at Tohoku University has developed a new hand-held land mine detection dual-sensor ALIS. ALIS is equipped with a metal detector and a GPR, and it has a sensor tracking system, which can record the GPR and Metal detector signal with its location. It makes possible to process the data afterwards, including migration. The migration processing drastically increases the quality of the image of the buried objects. ALIS evaluation test was conducted in Croatia in October 2007. Then after, we stared a half-year evaluation test of ALIS in QC test in Croatia in December 2007. This test will be conducted in various soil and environmental conditions in Croatia.

Since 2002, we have developed a new hand-held land mine detection dual-sensor ALIS. ALIS is equipped with a metal detector and a GPR, and it has a sensor tracking system, which can record the GPR and Metal detector signal with its location. It makes possible to process the data afterwards, including migration. The migration processing drastically increases the quality of the image of the buried objects. The new system, we do not need any standard mark on the ground. Also, ALIS uses two different GPOR systems, including VNA (Vector Network Analyzer) based GPR and an Impulse GPR. VNA based GPR can provide better quality GPR images, although the impulse GPR is faster and light weight. ALIS evaluation tests were held in mine affected courtiers including Afghanistan, Croatia, Egypt and Cambodia. In the two-month evaluation test in Cambodia, ALIS worked without any problem. After some demonstrations and evaluation, we got many useful suggestions. Using these advises, we have modified the ALIS and it is now more easy to use. ALIS will be commercialized in 2007.

We are developing a new hand-held land mine detection dual-sensor (ALIS) which is equipped with a metal detector and a GPR. ALIS is equipped with a sensor tracking system, which can record the GPR and Metal detector signal with its location. It makes possible to process the data after the data was acquired, including migration. The migration processing drastically increases the quality of the images of the buried objects. Evaluation test of ALIS has been conducted in several test sites. In February 2006, a one-month evaluation test was conducted in Croatia, and in October- December 2006, a two-month evaluation test was conducted in Croatia. Since the dual-sensor is a new landmine detection sensor, and the conventional evaluation procedure developed for metal detectors cannot directly be applied for the dual sensor. In Croatia, the detection probability was comparable to that by a metal detector operated by local deminers. In addition, we showed that ALIS provides image of buried objects by GPR, which can be used for identification. Therefore, their performances were sufficiently high. Then the test was also conducted in Cambodia. The test was carried out by 2 local deminers independently, which allows studying the influence of different operators and increases the statistical value of the results.

In today's security conscious society the efficiency of biometric systems has an increasing tendency to replace the classic but less effective keys and passwords. Hand geometry readers are popular biometrics used for acces control and time and attendance applications. One of their weaknesses is vulnerability to spoofing using fake hands (latex, play-doh or dead-hands). The object of this paper is to design a feature to be added to the hand geometry scanner in order to detect vitality in the hand, reducing the possibilities for spoofing. This paper demonstrates how the hand reader was successfully spoofed and shows the implementation of the vitality detection feature through an inexpensive but efficient electronic design. The method used for detection is photo-plethysmography. The Reflectance Sensor built is of original conception. After amplifying, filtering and processing the sensor's signal, a message is shown via an LCD display, concerning the liveness of the hand and the pulse rate.© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The problem of tracking the motion of a functional, electrically controlled hand is addressed in this paper. We show that by using skin color and hand segments, the motion of a human hand controlled by a functional electrical stimulation (FES) system can be recovered and predicted. The hand motion tracking and prediction information can then be used as feedback in a closed loop control system to improve the control of the hand motion. We show how skin color tracking can be used to segment the human hand regions and how the hand segments can be used to identify the hand moving positions and how the changes of hand segments between two frames can be used to track the hand orientations. We then show how the hand motion can be recovered based on the changes of the hand positions and orientations and how the motion can be simulated and predicted. The tracking and motion identification methods are verified by the presentation of experimental results obtained using the methods described in the paper.

Second-harmonic-generation (SHG) microscopy is a powerful tool for in situ monitoring of collagen fibers in human skin. However, its practical use is still limited in the dermatological field due to the bulky and complicated setup. In this paper, we constructed a photonic-crystal-fiber-coupled, hand-held SHG microscope for in situ monitoring of collagen fibers in human skin. Fiber delivery of femtosecond pulse light was achieved by a large-mode-area photonic-crystal-fiber whereas the compact SHG microscopy setup was enclosed into a lens tube system. The combination of PCF with the lens tube system largely enhances the flexibility of measurement sites in the human skin.

Shape memory alloys (SMA) are a class of smart material having the unique ability to return to a predefined shape when heated. SMA based actuators have the potential to be very compact and low weight. As a result, much research has been devoted to the design of SMA based actuators; however, commercialization has been largely impeded by the small strain capacity inherent to SMA. To address this deficiency, this paper conveys the design of a large-strain SMA actuator (in excess of 30%) whose feasibility is investigated by integrating the actuators as artificial muscles in a two link anthropomorphic arm. The ensuing experimental results indicate that the actuators show great potential for a variety of emerging applications. Finally the design of an SMA based dextrous robotic hand evaluation facility is proposed, and provides a case study illustrating how smart structures provide a superior alternative to conventionally voluminous and heavy prosthetic actuators.

The Engineers Centre of Expertise of the Royal Netherlands Army (RNLA) has conducted a study on countermine in peace operations. This study, finished in 2002, concluded that the final solution to countermine will depend in the first place on better detection of buried low-metal mines, e.g. by direct detection of the explosive components in mines. Until such detection systems are available, intermediate solutions are necessary in order to assure freedom of movement in peace operations. Because countermine operations consist of a number of different activities (area preparation, detection, clearance, etc) and the suitability of the different types of available equipment depends on the scenario, the toolbox concept for countermine equipment was adopted. In 2003 a procurement process was started in order to fill this toolbox with commercial-off-the-shelf and military-off-the-shelf equipment. The paper gives a concise description of the study on countermine operations and the procurement process, and subsequently focuses on the set-up of the tests that were conducted in the framework of the procurement of hand-held mine detection systems, like metal detectors and dual-sensor mine detectors. Programs of requirements for these systems were drawn up, aiming at systems for general use and special purpose systems. Blind tests to check the compliancy to the detection performance requirements were designed and conducted in the short timeframe that was available in the procurement process. These tests are discussed in this paper, including the set-up of the test lanes, the targets used and their depths, and the role of the operator. The tests of the capability of the detectors to discriminate small targets adjacent to large targets were conducted according the guidelines of the CEN Workshop Agreement on metal detector tests. Although the results of the tests are commercially confidential, conclusions and lessons learned from the execution of these tests are presented

Multibiometric systems utilize the evidence presented by multiple biometric sources (e.g., face and fingerprint, multiple fingers of a user, multiple matchers, etc.) in order to determine or verify the identity of an individual. Information from multiple sources can be consolidated in several distinct levels, including the feature extraction level, match score level and decision level. While fusion at the match score and decision levels have been extensively studied in the literature, fusion at the feature level is a relatively understudied problem. In this paper we discuss fusion at the feature level in 3 different scenarios: (i) fusion of PCA and LDA coefficients of face; (ii) fusion of LDA coefficients corresponding to the R,G,B channels of a face image; (iii) fusion of face and hand modalities. Preliminary results are encouraging and help in highlighting the pros and cons of performing fusion at this level. The primary motivation of this work is to demonstrate the viability of such a fusion and to underscore the importance of pursuing further research in this direction.

Recently high brightness LED developed rapidly and would be a suitable replacement for hand-held projector compared with UHP lamp. Generally, uniformity and low etendue is required in illumination system of projection display, while the emitting distribution of HB-LED always has non-uniformity and large view angle. In this paper, we have designed a preliminary illuminator consisted of two curved reflective fly’s eyes especially for the lighting characteristic of HB-LED. By means of the asymmetric configuration we can get the small exit ray angle which reduces the etendue of illumination system. Because of reflective system, the embodiment is shorter than 20 mm. The uniformity is above 80% and the efficiency of the illuminator is better than 75%.

Deploying a world wide force that is strategically responsive and dominant at every point on the spectrum of conflict involves the cooperative system development and use of advanced technologies that yield revolutionary capabilities to support the war-fighters needs. This presentation describes an agent based control architecture and prototype implementation developed by ARDEC that enables command and control of multiple unmanned platforms and associated mission packages for collaborative target hand-off/engagement. Current prototypes provide the ability to remotely locate, track and predict the movement of enemy targets on the battlefield using a variety of sensor systems hosted on multiple, non-homogeneous SUAVs and UGVs.

The direct electroplanting makes many useless problems in the thermoplastic industry. One of these is an edge effects problem. The computer modeling helps to solve this problem. The direct influence of this problem's solution has electric field intension. It's involving dependence on potential distribution and current density distribution. The one from two different methods of the fluid's mixing is applied to analyze of fluid flow and concentration of ions. It shows how useful is the ability of solution's circulation and how it helps in the electrochemical covering technology.

Polarized light imaging can be used to map the borders of skin cancer that are invisible to the human eye. We designed a hand-held polarized-light camera that is sensitive to the superficial layers of the skin where cancer often arises. The camera system consists of two 8-bit CCD mounted on two sides of a polarizing beam splitter. An imaging lens mounted on the beam splitter collects light reflected from the skin. The collected light is divided into two states of polarization: parallel (PAR) and perpendicular (PER) to the incident light orientation. A custom-code combines images streaming from both cameras to yield an image based on the polarization ratio (PAR - PER)/(PAR + PER), which is sensitive to the superficial skin layer. Experiments in reflectance mode on micro-spheres solutions were conducted to test the system; Monte Carlo simulations of these experiments demonstrated excellent correlation. Early clinical work was conducted at the Oregon Health and Science University in the Dermatology department. Images of several skin lesions are presented.

The reconstruction of 3D objects from 2D line drawings is regarded as one of the key topics in the field of computer vision. The ongoing research is mainly focusing on the reconstruction of 3D objects that are mapped only from 2D straight lines, and that are symmetric in nature. Commonly, this approach only produces basic and simple shapes that are mostly flat or rather polygonized in nature, which is normally attributed to inability to handle curves. To overcome the above-mentioned limitations, a technique capable of handling non-symmetric drawings that encompass curves is considered. This paper discusses a novel technique that can be used to reconstruct 3D objects containing curved lines. In addition, it highlights an application that has been developed in accordance with the suggested technique that can convert a freehand sketch to a 3D shape using a mobile phone.

Application of machine vision is expected for efficiency and objectivity of inspection in various fields. Automation of visual inspection for asphalt pavement surface images is also expected, but it is difficult because of unexpected objects, non-uniform illumination and irregularities in the pavement surface. Many of conventional approaches are based on state-of-the-arts. However, there is a problem that the application conditions of these is limited. In this article, we proposed a new method based on state-of-the-art and machine learning for crack detection from asphalt pavement surface images. The classifier of the proposed method is the linear support vector machine, and it uses features proposed in the conventional study that is one of the state-of-the-art approaches. The proposed system need not a large number of training data, unlike deep learning architectures. It is easy to train the classifier to detect cracks using a GUI tool developed by authors. Quantitative evaluation using 100 road surface images obtained by mobile mapping system was performed to compare with our conventional method as one of state-of-the-art approaches. Experiments show that our proposed method clearly outperforms the state-of-the-art approach.

Human-Computer Interaction (HCI) raises demand of convenience, endurance, responsiveness and naturalness. This paper describes a design of a compact wearable low-power HCI equipment applied to gesture recognition. System combines multi-mode sense signals: the vision sense signal and the motion sense signal, and the equipment is equipped with the depth camera and the motion sensor. The dimension (40 mm × 30 mm) and structure is compact and portable after tight integration. System is built on a module layered framework, which contributes to real-time collection (60 fps), process and transmission via synchronous confusion with asynchronous concurrent collection and wireless Blue 4.0 transmission. To minimize equipment’s energy consumption, system makes use of low-power components, managing peripheral state dynamically, switching into idle mode intelligently, pulse-width modulation (PWM) of the NIR LEDs of the depth camera and algorithm optimization by the motion sensor. To test this equipment’s function and performance, a gesture recognition algorithm is applied to system. As the result presents, general energy consumption could be as low as 0.5 W.

Safety is a vital issue in Human-Robot Interaction (HRI). In order to guarantee safety in HRI, a model reference impedance control can be a very useful approach introducing a compliant control. In particular, this paper establishes a fuzzy logic compliance control (i.e. active compliance control) to reduce impact and forces during physical interaction between humans/objects and robots. Exploiting a virtual mass-spring-damper system allows us to determine a desired compliant level by understanding the behavior of the model reference impedance control. The performance of fuzzy logic compliant control is tested in simulation for a robotic hand known as the RED Hand. The results show that the fuzzy logic is a feasible control approach, particularly to control position and to provide compliant control. In addition, the fuzzy logic control allows us to simplify the controller design process (i.e. avoid complex computation) when dealing with nonlinearities and uncertainties.

This paper provides a comparative analysis of right handed people and left handed people when they write with both their hands. Two left handed and one right handed subject were asked to write their respective names on a paper using both, their left and right handed, and their brain signals were measured using EEG. Similarly, they were asked to perform simple mathematical calculations using both their hand. The data collected from the EEG from writing with both hands is compared. It is observed that though it is expected that the right brain only would contribute to left handed writing and vice versa, it is not so. When a right handed person writes with his/her left hand, the initial instinct is to go for writing with the right hand. Hence, both parts of the brain are active when a subject writes with the other hand. However, when the activity is repeated, the brain learns to expect to write with the other hand as the activity is repeated and then only the expected part of the brain is active.

Static hand gesture recognition (HGR) has drawn increasing attention in computer vision and human-computer interaction (HCI) recently because of its great potential. However, HGR is a challenging problem due to the variations of gestures. In this paper, we present a new framework for static hand gesture recognition. Firstly, the key joints of the hand, including the palm center, the fingertips and finger roots, are located. Secondly, we propose novel and discriminative features called root-center-angles to alleviate the influence of the variations of gestures. Thirdly, we design a distance metric called finger length weighted Mahalanobis distance (FLWMD) to measure the dissimilarity of the hand gestures. Experiments demonstrate the accuracy, efficiency and robustness of our proposed HGR framework.