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Relevant bibliographies by topics / Palm print Pattern

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Academic literature on the topic 'Palm print Pattern'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Palm print Pattern"

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Lubab, H. Albak, Rafi Omar Al-Nima Raid, and Hamid Salih Arwa. "Palm print verification based deep learning." TELKOMNIKA (Telecommunication, Computing, Electronics and Control) 19, no. 3 (2021): 851–57. https://doi.org/10.12928/telkomnika.v19i3.16573.

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In this paper, we consider a palm print characteristic which has taken wide attentions in recent studies. We focused on palm print verification problem by designing a deep network called a palm convolutional neural network (PCNN). This network is adapted to deal with two-dimensional palm print images. It is carefully designed and implemented for palm print data. Palm prints from the Hong Kong Polytechnic University Contact-free (PolyUC) 3D/2D hand images dataset are applied and evaluated. The results have reached the accuracy of 97.67%, this performance is superior and it shows that our propos

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Kanchana, S., and G. Balakrishnan. "Palm-Print Pattern Matching Based on Features Using Rabin-Karp for Person Identification." Scientific World Journal 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/382697.

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Palm-print based individual identification is regarded as an effectual method for identifying persons with high confidence. Palm-print with larger inner surface of hand contains many features such as principle lines, ridges, minutiae points, singular points, and textures. Feature based pattern matching has faced the challenge that the spatial positional variations occur between the training and test samples. To perform effective palm-print features matching, Rabin-Karp Palm-Print Pattern Matching (RPPM) method is proposed in this paper. With the objective of improving the accuracy of pattern m

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Pushpa, N. B., and N. B. Prajwala. "A Scientific Analysis to Observe Uniqueness in Lip Print Pattern." International Journal of Innovative Technology and Exploring Engineering 10, no. 4 (2021): 196–98. http://dx.doi.org/10.35940/ijitee.d8571.0210421.

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Every individual have their unique identification like palm print, signature, finger print, face recognition, lip print etc.. here in this research one such effort is made to analyses lip print and identify the individual using their lip print. The wrinkle and grooves pattern on the lips has individual characteristics like tongue prints, face recognition, iris pattern, fingerprints. Cheiloscopy is a forensic investigation technique that deals with identification of humans based on lips traces. Image processing technique is used, lip print of the individual is captured, processed and analyzed f

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Dr., N. B. Pushpa*, and Prajwala N.B. "A Scientific Analysis to Observe Uniqueness in Lip Print Pattern." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 10, no. 4 (2021): 196–98. https://doi.org/10.35940/ijitee.D8571.0210421.

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Every individual have their unique identification like palm print, signature, finger print, face recognition, lip print etc.. here in this research one such effort is made to analyses lip print and identify the individual using their lip print. The wrinkle and grooves pattern on the lips has individual characteristics like tongue prints, face recognition, iris pattern, fingerprints. Cheiloscopy is a forensic investigation technique that deals with identification of humans based on lips traces. Image processing technique is used, lip print of the individual is captured, processed and analyzed f

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Pranav Khare and Shristi Srivastava. "AI-Driven Palm Print Authentication: A comprehensive Analysis of Deep Learning Approaches for Efficient Biometrics." International Journal of Science and Research Archive 6, no. 1 (2022): 318–27. http://dx.doi.org/10.30574/ijsra.2022.6.1.0158.

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Palmprint recognition is a kind of biometric identification that confirms a person's identity by analyzing certain discriminative characteristics found on their palm. The benefits of contactlessness, stability, and security have made it a popular choice. This is why a palmprint is a reliable biometric for human identification due to its unique characteristics. The area of people recognition is only one of several that has benefited from the proliferation of better computer techniques and uses of artificial intelligence (AI). In this research, we survey the state-of-the-art in image processing

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Lawal, Aderonke, Segun Aina, Samuel Okegbile, Seun Ayeni, Dare Omole, and Adeniran Ishola Oluwaranti. "Palm Vein Recognition System Based on Derived Pattern and Feature Vectors." International Journal of Digital Literacy and Digital Competence 8, no. 2 (2017): 56–72. http://dx.doi.org/10.4018/ijdldc.2017040104.

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Biometrics is a technology for recognition under which Palm vein recognition stems. They are of crucial importance in various applications of high sensitivity. This article develops a palm vein recognition model, based on derived pattern and feature vectors. All the palm print images used in this work were obtained from CASIA Multi-Spectral Palmprint Image Database V1.0 (CASIA database). First, a Region of Interest (ROI) was identified and extracted from the palm print images. Next, Histogram Equalization was used to enhance the area of the palm print image in the Region of Interest. The enhan

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Li, Fang, Ying He, and Min Qi Zhang. "Automatic Schizophrenia Prediction Using Palm-Print Line Features." Applied Mechanics and Materials 519-520 (February 2014): 568–71. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.568.

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Palm-print has a wide range of applications in personal identification, disease diagnosis, and athletes selection. This paper focuses on automatic schizophrenia prediction based on the anomalies in the handprints of patients with schizophrenia. The application is an image processing system, which works on the basis of the relationship between palm print pattern and schizophrenia. The images of human palm form input to the system. Then, system applies digital image processing and analysis techniques on input images to identify certain features in the image. Based on the certain features capture

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Han, Chin-Chuan, Hsu-Liang Cheng, Chih-Lung Lin, and Kuo-Chin Fan. "Personal authentication using palm-print features." Pattern Recognition 36, no. 2 (2003): 371–81. http://dx.doi.org/10.1016/s0031-3203(02)00037-7.

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Kumar, V. D. Ambeth, V. D. Ashok Kumar, S. Malathi, and P. Jagaeedesh. "Intruder Identification Using Footprint Recognition with PCA and SVM Classifiers." Advanced Materials Research 984-985 (July 2014): 1345–49. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.1345.

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In modern digital era authentication has been done using biometric recognition. This biometric includes finger print, footprint, facial recognition, DNA of a person’s gene, hand palm print and eye’s iris recognition. The widely used among these is finger print and iris recognition. In this work we proposed a biometric recognition using footprints of a person. Earlier work deals with capturing footprint on a paper or on a surface. This won’t give us accurate foot print, since it depends on nature of the surface, quality of the paper and proper placement of the foot to give good foot print impre

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Mohit, Kumar Verma, and Saif Wajid Mohd. "A Multimodal Biometric System using Iris and Palmprint." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 1892–96. https://doi.org/10.35940/ijeat.C5236.029320.

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A biometric system is basically a system of image recognition that uses bio metric characteristics to identify individuals. The thesis introduces a biometric multimodal system that is based on iris-based Palm Print verification and fusion. We suggest an approach to extracting features from each modality using four-level decomposition of the wavelet packet. It includes 256 packets capable of generating a simple binary code. Dictate standardized thresholds based on the first three highest energy peaks that would impact 0 or 1 for each wavelet packet. Specific fusion approaches were evaluated at

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Dissertations / Theses on the topic "Palm print Pattern"

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楊子毅. "The study of pattern extraction and recognition based on finger-vein and palm-print." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/09751773561597304903.

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Books on the topic "Palm print Pattern"

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Fincham, Johnny. Modern Palm Reader: Reading Digits, Prints and Patterns to Reveal Personality. Quarto Publishing Group UK, 2020.

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Book chapters on the topic "Palm print Pattern"

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Sathiya, L., and V. Palanisamy. "A NEW APPROACH FOR FINGER KNUCKLE PRINT RECOGNITION USING DWTHT WITH KNN CLASSIFIER." In Futuristic Trends in Artificial Intelligence Volume 3 Book 11. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bkai11p5ch1.

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In Present Numerous scientific research based on biometric applications like face, iris, voice, hand-based biometrics traits like palm print and fingerprint technique are employed for maculating the individuals. These distinct biometrics habits have their development and flaw so that no particular biometrics can pleasantly enough to opt for all terms like the accuracy and cost of all applications. In recent times, distinct hand-based biometrics technique such as Finger Knuckle Print (FKP) has been addressed for booming the attention among biometric researchers. The image template pattern forma

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Mercy, J. Sheela, and S. Silvia Priscila. "Efficient Noise Removal in Palmprint Images Using Various Filters in a Machine-Learning Approach." In Explainable AI Applications for Human Behavior Analysis. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1355-8.ch011.

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A biological identification technique, palm print identification, takes advantage of the distinctive patterns on a person's palm for authentication. It falls under the broader category of biometrics, which deals with evaluating and statistically assessing each individual's distinctive personality characteristics. The efficiency of three well-known noise-removal methods the non-local mean (NLM) filter, Wiener filter, and median filter when utilized on palmprint images are examined in the present research. Peak signal-to-noise ratio (PSNR), mean squared error (MSE), and structural similarity ind

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Dastidar, Jayati Ghosh, Debangshu Chakraborty, Soumen Mukherjee, and Arup Kumar Bhattacharjee. "Analysis of Human Gait for Designing a Recognition and Classification System." In Intelligent Innovations in Multimedia Data Engineering and Management. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7107-0.ch008.

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Identification and recognition of a human subject by monitoring a video/image by using various biometric features such as fingerprints, retina/iris scans, palm prints have been of interest to researches. In this chapter, an attempt has been made to recognize a human subject uniquely by monitoring his/her gait. This has been done by analyzing sampled frames of a video sequence to first detect the presence of a human form and then extract the silhouette of the subject in question. The extracted silhouette is then used to find the skeleton from it. The skeleton contains a set of points that retai

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Conference papers on the topic "Palm print Pattern"

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Yang, Jun, and Xianhong Zhao. "Palm print image processing with PCNN." In International Conference on Image Processing and Pattern Recognition in Industrial Engineering, edited by Zhengyu Du and Bin Liu. SPIE, 2010. http://dx.doi.org/10.1117/12.867026.

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Kumar, Amioy, M. Hanmandlu, Vamsi K. Madasu, and Shantaram Vasikarla. "A palm print authentication system using quantized phase feature representation." In 2011 IEEE Applied Imagery Pattern Recognition Workshop: Imaging for Decision Making (AIPR 2011). IEEE, 2011. http://dx.doi.org/10.1109/aipr.2011.6176353.

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Hanmandlu, M., Ankit Gureja, and Ankur Jain. "Palm print recognition using Local Binary Pattern operator and support vector machines." In 2010 International Conference on Signal and Image Processing (ICSIP). IEEE, 2010. http://dx.doi.org/10.1109/icsip.2010.5697461.

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Wibawa, Prasetya Aria, B. W. Tjokorda Agung, and Febryanti Sthevanie. "Palm print recognition using competitive hand valley detection, local binary pattern and probabilistic neural network." In 2014 International Conference on Information Technology Systems and Innovation (ICITSI). IEEE, 2014. http://dx.doi.org/10.1109/icitsi.2014.7048246.

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Reports on the topic "Palm print Pattern"

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Varastehpour, Soheil, Hamid Sharifzadeh, Iman Ardekani, and Abdolhossein Sarrafzadeh. Human Biometric Traits: A Systematic Review Focusing on Vascular Patterns. Unitec ePress, 2020. http://dx.doi.org/10.34074/ocds.086.

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Authentication methods based on human traits, including fingerprint, face, iris, and palm print, have developed significantly, and currently they are mature enough to be reliably considered for human identification purposes. Recently, as a new research area, a few methods based on non-facial skin features such as vein patterns have been developed. This literature review paper explores some key biometric systems such as face recognition, iris recognition, fingerprint, and palm print, and discusses their respective advantages and disadvantages; then by providing a comprehensive analysis of these

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