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Journal articles on the topic 'The image of hand'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Hegdé, Jay, Nicholas J. Tustison, William T. Parker, Fallon Branch, Nathan Yanasak, and Lorie A. Stumpo. "An Anatomical Template for the Normalization of Medical Images of Adult Human Hands." Diagnostics 13, no. 12 (2023): 2010. http://dx.doi.org/10.3390/diagnostics13122010.

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During medical image analysis, it is often useful to align (or ‘normalize’) a given image of a given body part to a representative standard (or ‘template’) of that body part. The impact that brain templates have had on the analysis of brain images highlights the importance of templates in general. However, templates for human hands do not exist. Image normalization is especially important for hand images because hands, by design, readily change shape during various tasks. Here we report the construction of an anatomical template for healthy adult human hands. To do this, we used 27 anatomicall

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He, Wangyong, Zhongzhao Xie, Yongbo Li, Xinmei Wang, and Wendi Cai. "Synthesizing Depth Hand Images with GANs and Style Transfer for Hand Pose Estimation." Sensors 19, no. 13 (2019): 2919. http://dx.doi.org/10.3390/s19132919.

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Hand pose estimation is a critical technology of computer vision and human-computer interaction. Deep-learning methods require a considerable amount of tagged data. Accordingly, numerous labeled training data are required. This paper aims to generate depth hand images. Given a ground-truth 3D hand pose, the developed method can generate depth hand images. To be specific, a ground truth can be 3D hand poses with the hand structure contained, while the synthesized image has an identical size to that of the training image and a similar visual appearance to the training set. The developed method,

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Zhang, Haozhuo, Bin Zhu, Yu Cao, and Yanbin Hao. "Hand1000: Generating Realistic Hands from Text with Only 1,000 Images." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 9 (2025): 9905–13. https://doi.org/10.1609/aaai.v39i9.33074.

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Text-to-image generation models have achieved remarkable advancements in recent years, aiming to produce realistic images from textual descriptions. However, these models often struggle with generating anatomically accurate representations of human hands. The resulting images frequently exhibit issues such as incorrect numbers of fingers, unnatural twisting or interlacing of fingers, or blurred and indistinct hands. These issues stem from the inherent complexity of hand structures and the difficulty in aligning textual descriptions with precise visual depictions of hands. To address these chal

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Chyad, Haitham Salman, Raniah Ali Mustafa, and Kawther Thabt Saleh. "Hand Print Recognition System based on FP-Growth Algorithm." Webology 19, no. 1 (2022): 980–1000. http://dx.doi.org/10.14704/web/v19i1/web19067.

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Hand print recognition system received great interest in the recent few years such as human-computer interaction, computer vision, and computer graphics. In this paper, proposed system for recognition human handprint based on FP-growth algorithm, the system consists of three-stage. The first stage the detection algorithm using HSV color space, canny algorithm and contrast enhancement for grayscale. In this stage separate skin area in-handprint image through first HSV color space converting RGB to HSV color space as well as conducting specific rules for determining the skin area. And then appli

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Ju, Shengtai, Amy R. Reibman, and Amanda J. Deering. "Robust hand hygiene monitoring for food safety using hand images." Electronic Imaging 35, no. 7 (2023): 275–1. http://dx.doi.org/10.2352/ei.2023.35.7.image-275.

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Pavani, Francesco, and Massimiliano Zampini. "The Role of Hand Size in the Fake-Hand Illusion Paradigm." Perception 36, no. 10 (2007): 1547–54. http://dx.doi.org/10.1068/p5853.

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When a hand (either real or fake) is stimulated in synchrony with our own hand concealed from view, the felt position of our own hand can be biased toward the location of the seen hand. This intriguing phenomenon relies on the brain's ability to detect statistical correlations in the multisensory inputs (ie visual, tactile, and proprioceptive), but it is also modulated by the pre-existing representation of one's own body. Nonetheless, researchers appear to have accepted the assumption that the size of the seen hand does not matter for this illusion to occur. Here we used a real-time video imag

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Pornpanomchai, Chomtip. "Image-Based Hand Tools and Accessories Recognition by ResNet50." International Journal of Membrane Science and Technology 10, no. 2 (2023): 3620–29. http://dx.doi.org/10.15379/ijmst.v10i2.3193.

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The objective of this research is to create a computer system which can recognize various kinds of hand-tools by using only a single image. The developed system is called “Hand-tool and accessory image recognition system or (HTAIRS)”. The system consists of 4 main modules, namely: 1) dataset training, 2) image acquisition, 3) image recognition, and 4) result presentation modules. The system employs the convolutional neural networks (CNN) called “ResNet50”, which is a toolbox in MATLAB software. The developed system creates its own dataset called “Hand Tools Dataset”, which consists of 165 diff

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Shibuya, Satoshi. "Effects of Orientation and Appearance of a Synchronously Moving Object on Hand Movements." Psych 2, no. 4 (2020): 287–95. http://dx.doi.org/10.3390/psych2040022.

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Various devices have been developed to enable humans to control remote objects using active hand movements. However, it is still unclear how the visual characteristics of a synchronously moving object influences hand movements. This study investigates the effects of visual appearance and orientation of a hand-controlled object on hand movements using a novel visuomotor task. The motion of a visual image on a monitor reflected the participants’ right hand movements in the forwards-backwards direction, but not in the lateral direction (i.e., the lateral position of the image was fixed). Particip

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Tomida, Motomasa, and Kiyoshi Hoshino. "Visual-Servoing Control of Robot Hand with Estimation of Full Articulation of Human Hand." Key Engineering Materials 625 (August 2014): 728–35. http://dx.doi.org/10.4028/www.scientific.net/kem.625.728.

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A depth sensor or depth camera is available at a reasonable cost in recent years. Due to the excessive dispersion of depth values outputted from the depth camera, however, changes in the pose cannot be directly employed for complicated hand pose estimation. The authors therefore propose a visual-servoing controlled robotic hand with RGB high-speed cameras. Two cameras have their own database in the system. Each data set has proportional information of each hand image and image features for matching, and joint angle data for output as estimated results. Once sequential hand images are recorded

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Guru, D. S., K. B. Nagasundara, S. Manjunath, and R. Dinesh. "An Approach for Hand Vein Representation and Indexing." International Journal of Digital Crime and Forensics 3, no. 2 (2011): 1–15. http://dx.doi.org/10.4018/jdcf.2011040101.

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This paper proposes a model for representing and indexing of hand vein images. The proposed representation model identifies the junction points and perceives the spatial relationships existing among all junction points in hand vein images by the use of triangular spatial relationship (TSR). The model preserves the TSR among the junction points in a symbolic hand vein image by the use of quadruples and for each quadruple, a unique TSR key is generated. A novel methodology to label the junction points based on graph properties of junction points is also proposed. A Symbolic Hand Vein Image Datab

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Vaishnavi D. A., Lavanya, Anil Kumar C., Harish S., and Divya M. L. "MediaPipe to Recognise the Hand Gestures." WSEAS TRANSACTIONS ON SIGNAL PROCESSING 18 (July 2, 2022): 134–39. http://dx.doi.org/10.37394/232014.2022.18.19.

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Human Computer Interaction (HCI) can be improved drastically using the hand gesture based recognition system. This system is designed to detect the gestures of the hands in the images captured in real time. There are certain areas of intersect in the hands that are there for the classification. The gaming devices like Xbox, PS4 and smart phones are also using this method to solve few problems. In this paper a smart method i9s developed to solve the problem. Using Python 3.9 and MediaPipe, the hand gestures are recognised in the real-time images. The background subtraction is the key method use

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Yan, Licheng, Lu Leng, Andrew Beng Jin Teoh, and Cheonshik Kim. "A Realistic Hand Image Composition Method for Palmprint ROI Embedding Attack." Applied Sciences 14, no. 4 (2024): 1369. http://dx.doi.org/10.3390/app14041369.

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Palmprint recognition (PPR) has recently garnered attention due to its robustness and accuracy. Many PPR methods rely on preprocessing the region of interest (ROI). However, the emergence of ROI attacks capable of generating synthetic ROI images poses a significant threat to PPR systems. Despite this, ROI attacks are less practical since PPR systems typically take hand images as input rather than just the ROI. Therefore, there is a pressing need for a method that specifically targets the system by composing hand images. The intuitive approach involves embedding an ROI into a hand image, a comp

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KUMAR, SANJAY, DINESH K. KUMAR, ARUN SHARMA, and NEIL McLACHLAN. "VISUAL HAND GESTURES CLASSIFICATION USING WAVELET TRANSFORMS." International Journal of Wavelets, Multiresolution and Information Processing 01, no. 04 (2003): 373–92. http://dx.doi.org/10.1142/s0219691303000232.

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This paper presents a novel technique for classifying human hand gestures based on stationary wavelet transform (SWT) and compares the results with classification based on Hu moments. The technique uses view-based approach for representation of hand actions, and artificial neural networks (ANN) for classification. This approach uses a cumulative image-difference technique where the time between the sequences of images is implicitly captured in the representation of action. This results in the construction of Motion History Images (MHI). These MHI's are decomposed into four sub-images using SWT

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V V, Nivedha, and Suganya K S. "Ml Based Hand Gesture Recognition." Indian Journal of Computer Science and Technology 2, no. 3 (2023): 01–07. http://dx.doi.org/10.59256/indjcst.20230203001.

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The projects focus on Gesture recognition using the media pipe hands Lite framework where the custom data set of 10 gesture Images is trained with an in built media pipe hands model which contains 2CNN models-A palm detection model running on single Shot detection architecture and a hand landmark generator running on regression model architecture. The data set is successfully trained and tested with the proposed method and an accuracy of 98 percent is obtained. Keywords: Gesture Recognition, Media pipe, Hands De-tection, CNN, Regression Model, Hand Landmark Detection, Machine Learning, Image P

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SU, C. "Hand image recognition by the techniques of hand shape scaling and image weight scaling." Expert Systems with Applications 34, no. 4 (2008): 2976–87. http://dx.doi.org/10.1016/j.eswa.2007.05.040.

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Or, Etay, and Dmitry Pundik. "Hand Motion and Image Stabilization in Hand-held Devices." IEEE Transactions on Consumer Electronics 53, no. 4 (2007): 1508–12. http://dx.doi.org/10.1109/tce.2007.4429245.

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Nguyen, Huy Sinh, and Hai Vu. "Hand Detection and Segmentation in First Person Image Using Mask R-CNN." Research and Development on Information and Communication Technology 2022, no. 1 (2022): 1–11. http://dx.doi.org/10.32913/mic-ict-research.v2022.n1.1001.

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In this work, we propose a technique to automatically detect and segment hands on first-person images of patientsin upper limb rehabilitation exercises. The aim is to automate the assessment of the patient's recovery processthrough rehabilitation exercises. The proposed technique includes the following steps: 1) setting up a wearablecamera system and collecting upper extremity rehabilitation exercise data. The data is filtered, selected andannotated with the left and right hand as well as segmented the image area of the patient's hand. The datasetconsists of 3700 images with the name RehabHand

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Chen, Jing, Lin Yang, Yim-Wah Mak, et al. "Hand Hygiene Education Components Among First-Year Nursing Students." JAMA Network Open 7, no. 6 (2024): e2413835. http://dx.doi.org/10.1001/jamanetworkopen.2024.13835.

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ImportanceFew studies have directly and objectively measured the individual and combined effects of multifaceted hand hygiene education programs.ObjectiveTo evaluate the individual and combined immediate effects of an instructional video and hand scan images on handwashing quality, decontamination, and knowledge improvement.Design, Setting, and ParticipantsThis cluster randomized clinical trial was conducted in June to July 2023 among first-year nursing students at a university in Hong Kong. The study used an intention-to-treat analysis.InterventionHand hygiene education sessions featuring an

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Mankar, Dushyant, and Dr. P.S. Chaudhary. "Tongue Image Diagnosis System using Machine Learning with Hand-Crafted Features." International Journal of Preventive Medicine and Health 4, no. 6 (2024): 1–6. https://doi.org/10.54105/ijpmh.l1097.04060924.

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Traditional Chinese Medicine theorizes a clear relationship between the visual characteristics of the tongue and the operational condition of the body's organs. The visual characteristics of the tongue can offer important indications for diagnosing diseases. Investigating tongue image processing methods for automated disease identification is a flourishing field of study in the modernization of Traditional Chinese Medicine. Although autonomous extraction of high-dimensional features is inherently more beneficial in deep learning than in conventional methods, its usefulness in medical image ana

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Dushyant, Mankar. "Tongue Image Diagnosis System using Machine Learning with Hand-Crafted Features." International Journal of Preventive Medicine and Health (IJPMH) 4, no. 6 (2024): 1–6. https://doi.org/10.54105/ijpmh.L1097.04060924.

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<strong>Abstract: </strong>Traditional Chinese Medicine theorizes a clear relationship between the visual characteristics of the tongue and the operational condition of the body's organs. The visual characteristics of the tongue can offer important indications for diagnosing diseases. Investigating tongue image processing methods for automated disease identification is a flourishing field of study in the modernization of Traditional Chinese Medicine. Although autonomous extraction of high-dimensional features is inherently more beneficial in deep learning than in conventional methods, its usef

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Ding, You Dong, and Hai Bo Pang. "An Improved Algorithm of Hand-Gesture Recognition Based on Haar-Like Features and Adaboost." Advanced Materials Research 588-589 (November 2012): 1238–41. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1238.

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In this paper, we proposed an improved algorithm of hand-gesture recognition based on Haar-like features and Adaboost. Initial, we calculated the Haar-like features of hand-gesture images by integral image. Then, we used the principal components analysis method to reduce the dimension of Haar-like features. At last, an Adaboost classifier performed the hand-gesture recognition task with the hand-gesture features. A dataset with large hand gestures (12 types, 600 hand-gesture images) was built, including some large pose-angle (about 40 deg.) hand-gesture images. Our experiment results demonstra

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Xu, Chi, Wendi Cai, Yongbo Li, Jun Zhou, and Longsheng Wei. "Accurate Hand Detection from Single-Color Images by Reconstructing Hand Appearances." Sensors 20, no. 1 (2019): 192. http://dx.doi.org/10.3390/s20010192.

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Hand detection is a crucial pre-processing procedure for many human hand related computer vision tasks, such as hand pose estimation, hand gesture recognition, human activity analysis, and so on. However, reliably detecting multiple hands from cluttering scenes remains to be a challenging task because of complex appearance diversities of dexterous human hands (e.g., different hand shapes, skin colors, illuminations, orientations, and scales, etc.) in color images. To tackle this problem, an accurate hand detection method is proposed to reliably detect multiple hands from a single color image u

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Ogiela, Marek R., Ryszard Tadeusiewicz, and Lidia Ogiela. "Graph image language techniques supporting radiological, hand image interpretations." Computer Vision and Image Understanding 103, no. 2 (2006): 112–20. http://dx.doi.org/10.1016/j.cviu.2006.04.001.

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Putnikovic, Biljana, Ivan Stankovic, Predrag Milicevic, Miloje Marjanovic, and Aleksandar Neskovic. "Hand-held echo is not so handy in everyone’s hands: Misdiagnosing congenital septal defects in patients with heart murmurs." Srpski arhiv za celokupno lekarstvo 143, no. 5-6 (2015): 322–25. http://dx.doi.org/10.2298/sarh1506322p.

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Introduction. Echocardiography is a highly operator-dependant technique which requires adequate training and skills that are frequently not present, considering the widespread use of cardiovascular ultrasound. This could particularly be true for hand-held echo devices which made echocardiography more accessible but are frequently used by non-cardiologists and non-experts. Outline of Cases. We present a 45-year-old female and a 37-year-old male with heart murmurs due to atrial and ventricular septal defect, respectively. Congenital septal defects were undiagnosed in both patients during several

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Mario, Gazziro, Vasques Matheus, Real Eduardo, Carmo João, and Kunkel Maria. "Automatic Hand Features Extraction for Forensic Purposes." Journal of Forensic Science and Research 7, no. 1 (2023): 077–82. http://dx.doi.org/10.29328/journal.jfsr.1001054.

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This work describes a low computational cost image processing methodology for the identification of hand features for forensic applications – like height, gender, and ethnicity for suspect inference. The proposed methodology provides an adequately tailored sequence of image and geometrical processings on pictures of hands based on critical points like fingertips, finger valleys, and palm centers. As a result, we present the automatic measurements taken on 416 images compared with actual measurements from a manual caliper. The proposed approach leads to a 93.16% correlation (p - value < 0.05

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Mishra, Abhinav, Amit Katoch, Abhay Tiwari, and Himanshu Kumar. "Hand Gesture Image Drag and Drop." Recent Trends in Artificial Intelligence & its Applications 1, no. 2 (2022): 21–25. http://dx.doi.org/10.46610/rtaia.2022.v01i02.004.

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The project ‘Virtual Drag’ (Artificial Intelligence) is a OpenCV based system. This will allow the user to virtually click and drag the pictures and items on the screen to other parts of the screen without use of mouse. The system will detect the hand landmarks on the palm, using those pin points and distance between the fingertips the system will be able to perform the operation. Virtual Drag utilizes the prominent gestures of your hand to drag and drop the images from one place to another. User needs to snap the fingers together to pick the image and then drag to any part of the screen and t

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Precht, Helle, Claus Bjørn Outzen, Martin Weber Kusk, Malene Bisgaard, and Dag Waaler. "COMPARISON OF CONVENTIONAL HAND EXAMINATION ON SIX OPTIMISED DR SYSTEMS." Radiation Protection Dosimetry 194, no. 1 (2021): 27–35. http://dx.doi.org/10.1093/rpd/ncab067.

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Abstract The purpose of this study was to investigate the challenges in comparing digital radiography (DR) systems from different vendors for various combinations of exposure factors in posterior–anterior hand radiographs. Image quality was evaluated for a range of tube voltages and tube current-time products using a technical contrast-detail (CDRAD) phantom and an anthropomorphic hand phantom. 900 technical CDRAD images were analysed providing quality figures of merit (IQFinv) and two experienced reporting radiographers using visual grading analysis (VGA) scored 108 anthropomorphic images. Th

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Haider, Syed Aqeel, Yawar Rehman, and S. M. Usman Ali. "Enhanced Multimodal Biometric Recognition Based upon Intrinsic Hand Biometrics." Electronics 9, no. 11 (2020): 1916. http://dx.doi.org/10.3390/electronics9111916.

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In the proposed study, we examined a multimodal biometric system having the utmost capability against spoof attacks. An enhanced anti-spoof capability is successfully demonstrated by choosing hand-related intrinsic modalities. In the proposed system, pulse response, hand geometry, and finger–vein biometrics are the three modalities of focus. The three modalities are combined using a fuzzy rule-based system that provides an accuracy of 92% on near-infrared (NIR) images. Besides that, we propose a new NIR hand images dataset containing a total of 111,000 images. In this research, hand geometry i

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Zhang, Zhongqun, Yihua Cheng, Eduardo Pérez-Pellitero, et al. "Single-view Image to Novel-view Generation for Hand-Object Interactions." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 10 (2025): 10394–402. https://doi.org/10.1609/aaai.v39i10.33128.

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Hand-object interaction modeling from a single RGB image is a significantly challenging task. Previous works typically reconstruct hand-object interactions as texture-less meshes, ignoring photo-realistic image generation. In this work, we introduce the HO123, a novel method to synthesize novel-view hand-object interaction images from a single image. To this end, we first train a 2D diffusion prior. Given the camera pose in novel views, our approach transfers the camera information into explicit hand representations, including hand depth and skeleton images. We propose a global hand embedding

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Wang, Yinqiao, Hao Xu, Pheng Ann Heng, and Chi-Wing Fu. "SiMA-Hand: Boosting 3D Hand-Mesh Reconstruction by Single-to-Multi-View Adaptation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 6 (2024): 5704–12. http://dx.doi.org/10.1609/aaai.v38i6.28382.

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Estimating 3D hand mesh from RGB images is a longstanding track, in which occlusion is one of the most challenging problems. Existing attempts towards this task often fail when the occlusion dominates the image space. In this paper, we propose SiMA-Hand, aiming to boost the mesh reconstruction performance by Single-to-Multi-view Adaptation. First, we design a multi-view hand reconstructor to fuse information across multiple views by holistically adopting feature fusion at image, joint, and vertex levels. Then, we introduce a single-view hand reconstructor equipped with SiMA. Though taking only

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Fujiwara, Kengo, Rikako Shimoda, Masatomo Shibata, Yoshinaga Awano, Koji Shibayama, and Toshio Higashi. "A Method for Using Video Presentation to Increase Cortical Region Activity during Motor Imagery Tasks in Stroke Patients." Brain Sciences 13, no. 1 (2022): 29. http://dx.doi.org/10.3390/brainsci13010029.

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Previous studies have reported that stroke patients have difficulty recalling the motor imagery (MI) of a task, also known as MI vividness. Research on combining MI with action observation is gaining importance as a method to improve MI vividness. We enrolled 10 right-handed stroke patients and compared MI vividness and cortical activity under different presentation methods (no inverted image, inverted image of another individual’s hand, and an inverted image of the patient’s nonparalyzed hand) using near-infrared spectroscopy. Images of the nonparalyzed upper limb were inverted to make the pa

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Ji, Peng, Xianjian Wang, Fengying Ma, Jinxiang Feng, and Chenglong Li. "A 3D Hand Attitude Estimation Method for Fixed Hand Posture Based on Dual-View RGB Images." Sensors 22, no. 21 (2022): 8410. http://dx.doi.org/10.3390/s22218410.

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This work provides a 3D hand attitude estimation approach for fixed hand posture based on a CNN and LightGBM for dual-view RGB images to facilitate the application of hand posture teleoperation. First, using dual-view cameras and an IMU sensor, we provide a simple method for building 3D hand posture datasets. This method can quickly acquire dual-view 2D hand image sets and automatically append the appropriate three-axis attitude angle labels. Then, combining ensemble learning, which has strong regression fitting capabilities, with deep learning, which has excellent automatic feature extraction

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Beugnet, Martine, and Kriss Ravetto-Biagioli. "The Image Book." Alphaville: Journal of Film and Screen Media, no. 23 (July 15, 2022): 10–31. http://dx.doi.org/10.33178/alpha.23.01.

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Drawing inspiration from Denis de Rougemont’s 1936 text Penser avec les mains, Jean-Luc Godard’s most recent film brings together what the Swiss philosopher calls “penser engagé” with his own unique kind of “cinéma engagé.” The Image Book (Le Livre d’image, 2018) starts with three image-gestures that punctuate the film: the cropped close-up of the right hand of Leonardo da Vinci’s St. John The Baptist, French illustrator Joseph Pinchon’s drawing of Bécassine with her upwards pointing left hand, and the hands of the filmmaker joining together spools of film at a Steenbeck editing table. Like ma

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FUKE, SAWA, MASAKI OGINO, and MINORU ASADA. "BODY IMAGE CONSTRUCTED FROM MOTOR AND TACTILE IMAGES WITH VISUAL INFORMATION." International Journal of Humanoid Robotics 04, no. 02 (2007): 347–64. http://dx.doi.org/10.1142/s0219843607001096.

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This paper proposes a learning model that enables a robot to acquire a body image for parts of its body that are invisible to itself. The model associates spatial perception based on motor experience and motor image with perception based on the activations of touch sensors and tactile image, both of which are supported by visual information. The tactile image can be acquired with the help of the motor image, which is thought to be the basis for spatial perception, because all spatial perceptions originate in motor experiences. Based on the proposed model, a robot estimates invisible hand posit

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Shen, Xiang, Feng Zhu, Zhi Sun, and Shuli Zhao. "Research on Bone Age Automatic Judgment Algorithm Based on Deep Learning and Hand X-ray Image." Journal of Medical Imaging and Health Informatics 11, no. 1 (2021): 156–61. http://dx.doi.org/10.1166/jmihi.2021.3443.

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Objective: To learn the depth of paper using feature extraction, combined with critical areas of heat syndrome and related information, X-ray image of hand to analyze bone age children. Methods: The thesis of the X-ray image data preprocessing left hand, the use of depth of depth neural network learning methods, combined with clinical data skeletal age evaluation model to evaluate the effectiveness of the test model. Results: X-ray image of hand artificial feature extraction, combined SVM classification, automatic assessment of skeletal age. The method of automatic assessment of bone age SVM-b

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Tomida, Motomasa, and Kiyoshi Hoshino. "Wearable Device for High-Speed Hand Pose Estimation with a Ultrasmall Camera." Journal of Robotics and Mechatronics 27, no. 2 (2015): 167–73. http://dx.doi.org/10.20965/jrm.2015.p0167.

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<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/06.jpg"" width=""300"" /> Hand pose estimation with ultrasmall camera</div> Operating a robot intentionally by using various complex motions of the hands and fingers requires a system that accurately detects hand and finger motions at high speed. This study uses an ultrasmall camera and compact computer for development of a wearable device of hand pose estimation, also called a hand-capture device. The accurate estimations, however, require data matching with a large database. But a compact comput

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Nelikanti, Arjun. "Image Enhancement Using Image Fusion and Image Processing Techniques." COMPUSOFT: An International Journal of Advanced Computer Technology 03, no. 10 (2014): 1193–97. https://doi.org/10.5281/zenodo.14759375.

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Principle objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a multitude of choices for improving the visual quality of images. Appropriate choice of such techniques is greatly influenced by the imaging modality, task at hand and viewing conditions. This paper will provide a combination of two concepts, image fusion by DWT and digital image processing techniques. The enhanced image is validated using two parameters and this paper is implemented in MATLAB. 

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Morelli, L., F. Ioli, F. Maiwald, G. Mazzacca, F. Menna, and F. Remondino. "DEEP-IMAGE-MATCHING: A TOOLBOX FOR MULTIVIEW IMAGE MATCHING OF COMPLEX SCENARIOS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W4-2024 (February 14, 2024): 309–16. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w4-2024-309-2024.

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Abstract. Finding corresponding points between images is a fundamental step in photogrammetry and computer vision tasks. Traditionally, image matching has relied on hand-crafted algorithms such as SIFT or ORB. However, these algorithms face challenges when dealing with multi-temporal images, varying radiometry and contents as well as significant viewpoint differences. Recently, the computer vision community has proposed several deep learning-based approaches that are trained for challenging illumination and wide viewing angle scenarios. However, they suffer from certain limitations, such as ro

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Park, Ingyu, and Unjoo Lee. "Automatic, Qualitative Scoring of the Clock Drawing Test (CDT) Based on U-Net, CNN and Mobile Sensor Data." Sensors 21, no. 15 (2021): 5239. http://dx.doi.org/10.3390/s21155239.

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The Clock Drawing Test (CDT) is a rapid, inexpensive, and popular screening tool for cognitive functions. In spite of its qualitative capabilities in diagnosis of neurological diseases, the assessment of the CDT has depended on quantitative methods as well as manual paper based methods. Furthermore, due to the impact of the advancement of mobile smart devices imbedding several sensors and deep learning algorithms, the necessity of a standardized, qualitative, and automatic scoring system for CDT has been increased. This study presents a mobile phone application, mCDT, for the CDT and suggests

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Fang, Liyang, Jin Wang, Guodong Lu, Dongliang Zhang, and Jianhui Fu. "Hand-drawn grayscale image colorful colorization based on natural image." Visual Computer 35, no. 11 (2018): 1667–81. http://dx.doi.org/10.1007/s00371-018-1613-8.

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Satybaldina, Dina, and Gulzia Kalymova. "Deep learning based static hand gesture recognition." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 398. http://dx.doi.org/10.11591/ijeecs.v21.i1.pp398-405.

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Hand gesture recognition becomes a popular topic of deep learning and provides many application fields for bridging the human–computer barrier and has a positive impact on our daily life. The primary idea of our project is a static gesture acquisition from depth camera and to process the input images to train the deep convolutional neural network pre-trained on ImageNet dataset. Proposed system consists of gesture capture device (Intel® RealSense™ depth camera D435), pre-processing and image segmentation algorithms, feature extraction algorithm and object classification. For pre-processing and

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Satybaldina, Dina, and Gulzia Kalymova. "Deep learning based static hand gesture recognition." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 398–405. https://doi.org/10.11591/ijeecs.v21.i1.pp398-405.

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Hand gesture recognition becomes a popular topic of deep learning and provides many application fields for bridging the human-computer barrier and has a positive impact on our daily life. The primary idea of our project is a static gesture acquisition from depth camera and to process the input images to train the deep convolutional neural network pre-trained on ImageNet dataset. Proposed system consists of gesture capture device (Intel® RealSense™ depth camera D435), pre-processing and image segmentation algorithms, feature extraction algorithm and object classification. For preproce

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Wang, Xianghan, Jie Jiang, Yanming Guo, Lai Kang, Yingmei Wei, and Dan Li. "CFAM: Estimating 3D Hand Poses from a Single RGB Image with Attention." Applied Sciences 10, no. 2 (2020): 618. http://dx.doi.org/10.3390/app10020618.

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Precise 3D hand pose estimation can be used to improve the performance of human–computer interaction (HCI). Specifically, computer-vision-based hand pose estimation can make this process more natural. Most traditional computer-vision-based hand pose estimation methods use depth images as the input, which requires complicated and expensive acquisition equipment. Estimation through a single RGB image is more convenient and less expensive. Previous methods based on RGB images utilize only 2D keypoint score maps to recover 3D hand poses but ignore the hand texture features and the underlying spati

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Prakash, S. Saravana, P. Abinaya, and Lsuganthi . "Hand held Dermal Scanner." International Journal of Advance Research and Innovation 4, no. 4 (2016): 10–14. http://dx.doi.org/10.51976/ijari.441603.

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Dermatology is a branch of science dealing with the studies of skin, hair, nails etc. Nowadays skin disorders are more severe and many new disorders are emerging rapidly. Many devices are used for diagnostic as well as therapeutic applications. In this paper, we proposed a diagnostic device which is used to capture the images of affected skin surface through raspberry pi controller module with camera and display the image in LCD screen. The SD card is connected with module is used to store images for further analysis. Real time recording of the images can be obtained, viewed and stored for fur

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Himstead, Alexander S., Sean Melucci, Kevin M. Gustafson, Paul E. Israelsen, and Andrew Browne. "Feasibility of telemedicine program using a hand-held nonmydriatic retinal camera in Panama." International Journal of Ophthalmology 15, no. 6 (2022): 962–66. http://dx.doi.org/10.18240/ijo.2022.06.14.

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AIM: To evaluate the image quality of a telemedicine screening program for retinal disease using a nonmydriatic camera among rural island communities in Bocas del Toro, Panama. METHODS: In June 2018, a group of three medical students volunteered at clinics operated by the Floating Doctors in the province of Bocas del Toro, Panama. Non-mydriatic images of the retina were obtained using the Pictor Plus (Volk Optical, Mentor OH), randomized, and sent to two board-certified ophthalmologists at the University of California, Irvine for analysis using a modified version of the FOTO-ED scale. Inter-ra

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Chen, Jialing, Qingfen Hu, and Yi Shao. "A letter on a hand: Rotating together or separately?" Quarterly Journal of Experimental Psychology 72, no. 3 (2018): 472–80. http://dx.doi.org/10.1177/1747021818758264.

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The motor system plays a role in some object mental rotation tasks, and researchers have reported that people may use a strategy of motor simulation to mentally rotate objects. In this study, we used images of a hand with a letter printed on the palm to directly determine whether a hand image can be automatically rotated during the deliberate mental rotation of an object and whether the hand and object are rotated in the same trajectory. A total of 41 participants were shown the stimuli and asked to decide whether the letters, which were upright or tilted at specific degrees, were normal or mi

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Gorbovskaya, S. G. "Associative analysis of the painting by G. Moro “Salome, dancing before Herod” in the novel by J.-K. Huysmans “Against Nature”." Nauchnyi dialog 13, no. 2 (2024): 269–85. http://dx.doi.org/10.24224/2227-1295-2024-13-2-269-285.

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The phenomenon of the “symbolic image” is examined using the example of the flower in Salome’s hand in Gustave Moreau’s painting “Salome Dancing before Herod” and the lotus in Salome’s hand in J.-K. Huysmans’ novel “Against the Grain.” The history of the terms ‘imago’, ‘archetype’, and ‘symbolic image’ in psychoanalysis is traced, as well as the influence of these psychoanalytic concepts on the perception of imagery in literature and painting. The relevance of the study lies in the enduring interest of literary scholars in issues related to the interplay between psychoanalysis and literature,

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Saari, Jukka M., Markku T. Kerola, Markku Broas, and K. Matti Saari. "Hand-held digital video-camera for eye examination and follow-up." Journal of Telemedicine and Telecare 8, no. 4 (2002): 237–40. http://dx.doi.org/10.1258/135763302320272220.

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We developed a hand-held digital colour video-camera for eye examination in primary care. The device weighed 550 g. It featured a charge-coupled device (CCD) and corrective optics. Both colour video and digital still images could be taken. The video-camera was connected to a PC with software for database storage, image processing and telecommunication. We studied 88 normal subjects (38 male, 50 female), aged 7-62 years. It was not necessary to use mydriatic eye drops for pupillary dilation. Satisfactory digital images of the whole face and the anterior eye were obtained. The optic disc and the

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Fukui, Takao, Aya Murayama, and Asako Miura. "Recognizing Your Hand and That of Your Romantic Partner." International Journal of Environmental Research and Public Health 17, no. 21 (2020): 8256. http://dx.doi.org/10.3390/ijerph17218256.

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Although the hand is an important organ in interpersonal interactions, focusing on this body part explicitly is less common in daily life compared with the face. We investigated (i) whether a person’s recognition of their own hand is different from their recognition of another person’s hand (i.e., self hand vs. other’s hand) and (ii) whether a close social relationship affects hand recognition (i.e., a partner’s hand vs. an unknown person’s hand). For this aim, we ran an experiment in which participants took part in one of two discrimination tasks: (i) a self–others discrimination task or (ii)

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Zhang, Xun, Yong Hong Guo, Gang Li, and Jin Long He. "Vein Image Segmentation Based on One-Dimentional Gray and Filter Erosion Method." Applied Mechanics and Materials 635-637 (September 2014): 1049–55. http://dx.doi.org/10.4028/www.scientific.net/amm.635-637.1049.

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For the low contrast and serious noises, a fast image segmentation method based on one-dimensional gray segmentation, binary morphology erosion and area elimination is proposed. Since veins are thin and long, the vein image can be easily distinguished from background by judging the gray difference from nearby pixels when they are vertically or horizontally scanned. Then the processed image is diposed with erosion and area elimination to filter the noise. According to test results on the hand vein images which got from the equipment constructed by ourselves, it is proved that the method is more

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