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Journal articles on the topic 'Sauvola Thresholding'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Senthilkumaran, N1 and Vaithegi S2. "TOP 1 CITED PAPER - COMPUTER SCIENCE & ENGINEERING: AN INTERNATIONAL JOURNAL (CSEIJ)." COMPUTER SCIENCE & ENGINEERING: AN INTERNATIONAL JOURNAL (CSEIJ) 6, no. 1 (2019): 3. https://doi.org/10.5281/zenodo.3386005.

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Image binarization is the process of separation of pixel values into two groups, black as background and white as foreground. Thresholding can be categorized into global thresholding and local thresholding. This paper describes a locally adaptive thresholding technique that removes background by using local mean and standard deviation. Most common and simplest approach to segment an image is using thresholding. In this work we present an efficient implementation for threshoding and give a detailed comparison of Niblack and sauvola local thresholding algorithm. Niblack and sauvola thresholding

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Pambudi, Elindra Ambar, Abid Yanuar Badarudin, and Dimara Kusuma Hakim. "Analysis Thresholding Sauvola pada Background Subtraction untuk Deteksi Objek Bergerak." Jurnal Informatika 6, no. 2 (2019): 300–304. http://dx.doi.org/10.31311/ji.v6i2.6164.

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Metode segmentasi kebanyakan digunakan dalam teknik pengolahan citra yang berkaitan dengan deteksi objek bergerak. Segmentasi pada objek bergerak sangat penting untuk menentukan proses selanjutnya berupa pengenalan atau klasifikasi. Metode yang paling umum digunakan dalam teknik-teknik segmentasi adalah metode pengambangan. Metode pengambangan dibagi menjadi dua yaitu global dan lokal. Pada penelitian kali ini akan mencoba menggunakan salah satu metode pengambangan lokal adaptif yaitu sauvola. Sauvola akan digunakan sebagai nilai ambang dari background subtraction. Garis besar dari metode yang

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Chandrakala, M. "Image Analysis of Sauvola and Niblack Thresholding Techniques." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 2353–57. http://dx.doi.org/10.22214/ijraset.2021.34569.

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Image segmentation is a critical problem in computer vision and other image processing applications. Image segmentation has become quite challenging over the years due to its widespread use in a variety of applications. Image thresholding is a popular image segmentation technique. The segmented image quality is determined by the techniques used to determine the threshold value.A locally adaptive thresholding method based on neighborhood processing is presented in this paper. The performance of locally thresholding methods like Niblack and Sauvola was demonstrated using real-world images, print

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Anggraeni, Dessy Tri, and Condro Wibawa. "Perbaikan Citra Tanda Tangan Digital Menggunakan Metode Otsu Thressholding dan Sauvola." Jurnal Ilmiah Matrik 25, no. 1 (2023): 28–34. http://dx.doi.org/10.33557/jurnalmatrik.v25i1.2324.

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Abstract : The digital era forces people to digitize in all fields. Digital product that is often found is digital image. One kind of digital image application is the use of a digital image signature embedded in a document. However, often the results are unsatisfactory, such as background color problems, noise, lack of clarity, etc. The quality of digital image signatures can be improved by implementing the Otsu Thresholding and Sauvola methods. These two methods were chosen because they are widely used in document image quality improvement. The purpose of this study is to produce a better dig

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Yang, Yulong, Jin Yan, Jin Xu, et al. "Oil Film Detection for Marine Radar Image Using SBR Feature and Adaptive Threshold." Journal of Marine Science and Engineering 13, no. 6 (2025): 1178. https://doi.org/10.3390/jmse13061178.

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Marine oil spills pose a serious and persistent threat to marine ecosystems, coastal resources, and global environmental health. These incidents not only disrupt ecological balance by damaging marine flora and fauna but also lead to long-term economic consequences for fisheries, tourism, and maritime industries. Owing to their rapid spread and often unpredictable occurrence, timely and accurate detection is essential for effective containment and mitigation. An efficient detection system can significantly enhance the responsiveness of emergency teams, enabling targeted interventions that minim

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Chin, Ong Boon, Aimi Salihah Abdul Nasir, Ooi Wei Herng, and Erdy Sulino Mohd Muslim Tan. "Harumanis Mango Leaves Image Segmentation based on Wavelet Transformation with Phansalkar and Sauvola Thresholding." Journal of Physics: Conference Series 2107, no. 1 (2021): 012067. http://dx.doi.org/10.1088/1742-6596/2107/1/012067.

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Abstract Harumanis mango is one of the economic sources of the Perlis state. It has a sweeter taste compared to other mangoes. However, the Harumanis mango tree required specific weather, soil nutrient contents and pH level. This makes the farmer does not know the health condition of their Harumanis mango tree. Therefore, this project aims to provide the best method of leaves detection to the farmer. The leaves image samples are collecting from the orchard and undergo pre-processing. Then the input image was converted into grayscale with principal component analysis (PCA). Wavelet transformati

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Yuan, Boqi, Qinjun Wang, Jingyi Yang, Wentao Xu, and Chaokang He. "Granite Extraction Based on the SDGSAT-1 Satellite Thermal Infrared Spectrometer Imagery." Sensors 24, no. 6 (2024): 1750. http://dx.doi.org/10.3390/s24061750.

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Earth observation by remote sensing plays a crucial role in granite extraction, and many current studies use thermal infrared data from sensors such as ASTER. The challenge lies in the low spatial resolution of these satellites, hindering precise rock type identification. A breakthrough emerges with the Thermal Infrared Spectrometer (TIS) on the Sustainable Development Science Satellite 1 (SDGSAT-1) launched by the Chinese Academy of Sciences. With an exceptional 30 m spatial resolution, SDGSAT-1 TIS opens avenues for accurate granite extraction using remote sensing. This study, exemplified in

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Kiran, Mahreen, Imran Ahmed, Nazish Khan, and Alavalapati Goutham Reddy. "Chest X-ray segmentation using Sauvola thresholding and Gaussian derivatives responses." Journal of Ambient Intelligence and Humanized Computing 10, no. 10 (2019): 4179–95. http://dx.doi.org/10.1007/s12652-019-01281-7.

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Mohamad Roslan, Muhammad Ammar, Aimi Salihah Abdul Nasir, Marni Azira Markom, Allan Melvin Andrew, and Edy Victor Haryanto. "COVID-19 Chest X-Ray Lung Segmentation by Locally Adaptive Thresholding." Journal of Advanced Research in Applied Sciences and Engineering Technology 64, no. 3 (2025): 69–83. https://doi.org/10.37934/araset.64.3.6983.

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The novel coronavirus disease 2019 (COVID-19), first identified in December 2019 in Wuhan, China, rapidly escalated into a global pandemic. Effective and reliable solutions for automated detection and large-scale screening are crucial to monitor and control the spread of COVID-19. However, distinguishing between COVID-19 and pneumonia in chest X-ray (CXR) scans remains a challenge for radiologists due to overlapping image features. Additionally, modern diagnostic methods such as reverse transcription polymerase chain reaction (RT-PCR) are expensive, complex, and time-consuming. This study aims

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Saddami, Khairun, Khairul Munadi, Yuwaldi Away, and Fitri Arnia. "Improvement of binarization performance using local otsu thresholding." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 264. http://dx.doi.org/10.11591/ijece.v9i1.pp264-272.

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<p><span>Ancient document usually contains multiple noises such as uneven-background, show-through, water-spilling, spots, and blur text. The noise will affect the binarization process. Binarization is an extremely important process in image processing, especially for character recognition. This paper presents an improvement to Nina binarization technique. Improvements were achieved by reducing processing steps and replacing median filtering by Wiener filtering. First, the document background was approximated by using Wiener filter, and then image subtraction was applied. Furthermo

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Saddami, Khairun, Khairul Munadi, Yuwaldi Away, and Fitri Arnia. "Improvement of binarization performance using local otsu thresholding." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 264–72. https://doi.org/10.11591/ijece.v9i1.pp264-272.

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Ancients document usually contains multiple noises such as uneven background, show-through, water-spilling, spots, and blur text. The noise will affect the binarization process. Binarization is an extremely important process in image processing, especially for character recognition. This paper presents an improvement to Nina binarization technique. Improvements were achieved by reducing processing steps and replacing median filtering by Wiener filtering. First, the document background was approximated by using a Wiener filter, and then image subtraction was applied. Furthermore, the manuscript

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Roihan, Auliya Ulfattah, Nur Endah Sukmawati, Kusumaningrum Retno, and Adhy Satriyo. "Continuous speech segmentation using local adaptive thresholding technique in the blocking block area method." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 1 (2020): 407–18. https://doi.org/10.12928/TELKOMNIKA.v18i1.13958.

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Continuous speech is a form of natural human speech that is continuous without a clear boundary between words. In continuous speech recognition, a segmentation process is needed to cut the sentence at the boundary of each word. Segmentation becomes an important step because a speech can be recognized from the word segments produced by this process. The segmentation process in this study was carried out using local adaptive thresholding technique in the blocking block area method. This study aims to conduct performance comparisons for five local adaptive thresholding methods (Niblack, Sauvola,

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Phan Ngoc Khuong, Cat, Tien Tran Van, Quynh Nguyen Ngoc, Tu Ly Anh, Dung Tu Tuyet, and Anh Vu Quoc. "Segmentation of blood vessels in colposcopic images using polarized light and Sauvola thresholding." Science & Technology Development Journal - Engineering and Technology 3, no. 4 (2020): first. http://dx.doi.org/10.32508/stdjet.v3i4.673.

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Cervical cancer is one of the two most common gynecological cancers in the world, including breast cancer. Signs of cervical disease are usually the presence of atypical epithelium, superficial bleeding or abnormal vascular proliferation. Most of these signs are directly related to cervical intraepithelial neoplasia (CIN) and cervical cancer. Currently, to detect epithelial lesions as well as to observe the shape of blood vessels, the main diagnostic methods used are colposcopy and visual examination. This method has low sensitivity and specificity because subjective factors still exist and th

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Najafi, M. Hassan, and Mostafa E. Salehi. "A Fast Fault-Tolerant Architecture for Sauvola Local Image Thresholding Algorithm Using Stochastic Computing." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 24, no. 2 (2016): 808–12. http://dx.doi.org/10.1109/tvlsi.2015.2415932.

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Rofi'i, Mohammad, and Diah Rahayu Ningtias. "Local Adaptive Thresholding Menggunakan Metode Sauvola sebagai Tahapan Pra Pengolahan pada Data Citra Isyarat ECG." Jurnal Teori dan Aplikasi Fisika 10, no. 1 (2022): 103. http://dx.doi.org/10.23960/jtaf.v10i1.2904.

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Michalak, Hubert, and Krzysztof Okarma. "Fast Binarization of Unevenly Illuminated Document Images Based on Background Estimation for Optical Character Recognition Purposes." JUCS - Journal of Universal Computer Science 25, no. (6) (2019): 627–46. https://doi.org/10.3217/jucs-025-06-0627.

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One of the key operations during the image preprocessing step in Optical Character Recognition (OCR) algorithms is image binarization. Although for uniformly illuminated images, obtained typically by atbed scanners, the use of a single global threshold may be sufficient for further recognition of individual characters, it cannot be applied directly in case of non-uniform lightened document images. Such problem may occur during capturing photos of documents in unknown lighting conditions making a proper text recognition impossible in some parts of the image. Since the application of popular ada

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Van, Linh Nguyen, Giang V. Nguyen, Younghun Kim, et al. "Rapid Urban Flood Detection Using PlanetScope Imagery and Thresholding Methods." Water 17, no. 7 (2025): 1005. https://doi.org/10.3390/w17071005.

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With advances in optical satellite remote sensing, urban flood mapping (UFM) leveraging water’s distinct spectral characteristics for water identification is preferred and has gained more attention. PlanetScope’s daily 3 m resolution imagery enables detailed and time-sensitive flood monitoring. Unlike machine learning, which requires extensive training data, thresholding methods offer a faster and more adaptable solution for binary classification. Three global (Yen’s, Otsu’s, Isodata) and three local (Niblack, Sauvola, Gonzalez) thresholding methods, with their parameters optimized for each ca

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Thepade, Sudeep D., and Mangesh S. Dudhgaonkar Patil. "Improved classification of histopathological images with feature fusion of Thepade SBTC and Sauvola thresholding using machine learning." International Journal of Computational Vision and Robotics 15, no. 1 (2025): 118–36. https://doi.org/10.1504/ijcvr.2025.142925.

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Supriyanti, Retno, Muhammad Rifqi Kurniawan, Yogi Ramadhani, and Haris Budi Widodo. "Calculating the area of white spots on the lungs of patients with COVID-19 using the Sauvola thresholding method." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (2023): 315. http://dx.doi.org/10.11591/ijece.v13i1.pp315-324.

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<span lang="EN-US">COVID-19 is a pandemic that has occurred in the world since 2019. Researchers have carried out various ways in dealing with this disease, starting from the screening stage to the stage of treatment and therapy for COVID-19 patients. As the gateway to the COVID-19 problem, screening has an essential role in a diagnosis that leads to appropriate treatment. In this paper, we will focus on the screening stage using digital image processing techniques, namely in calculating the area of white spots in the lungs of COVID-19 patients. The white patches are an early indication

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Retno, Supriyanti, Rifqi Kurniawan Muhammad, Ramadhani Yogi, and Budi Widodo Haris. "Calculating the area of white spots on the lungs of patients with COVID-19 using the Sauvola thresholding method." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (2023): 315–24. https://doi.org/10.11591/ijece.v13i1.pp315-324.

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Coronavirus desease 2019 (COVID-19) is a pandemic that has occurred in the world since 2019. Researchers have carried out various ways in dealing with this disease, starting from the screening stage to the stage of treatment and therapy for COVID-19 patients. As the gateway to the COVID-19 problem, screening has an essential role in a diagnosis that leads to appropriate treatment. In this paper, we will focus on the screening stage using digital image processing techniques, namely in calculating the area of white spots in the lungs of COVID-19 patients. The white patches are an early indicatio

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Li, Zhongbo, Chao Yin, and Xixuan Zhang. "Crack Segmentation Extraction and Parameter Calculation of Asphalt Pavement Based on Image Processing." Sensors 23, no. 22 (2023): 9161. http://dx.doi.org/10.3390/s23229161.

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Crack disease is one of the most serious and common diseases in road detection. Traditional manual methods for measuring crack detection can no longer meet the needs of road crack detection. In previous work, the authors proposed a crack detection method for asphalt pavements based on an improved YOLOv5s model, which is a better model for detecting various types of cracks in asphalt pavements. However, most of the current research on automatic pavement crack detection is still focused on crack identification and location stages, which contributes little to practical engineering applications. B

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Kryjak, Tomasz, and Marek Gorgoń. "Parallel implementation of local thresholding in Mitrion-C." International Journal of Applied Mathematics and Computer Science 20, no. 3 (2010): 571–80. http://dx.doi.org/10.2478/v10006-010-0042-2.

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Parallel implementation of local thresholding in Mitrion-CMitrion-C based implementations of three image processing algorithms: a look-up table operation, simple local thresholding and Sauvola's local thresholding are described. Implementation results, performance of the design and FPGA logic utilization are discussed.

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CALZADA-NAVARRETE, V., and C. TORRES-HUITZIL. "A LOCAL ADAPTIVE THRESHOLD APPROACH TO ASSIST AUTOMATIC CHROMOSOME IMAGE SEGMENTATION." Latin American Applied Research - An international journal 44, no. 3 (2014): 277–82. http://dx.doi.org/10.52292/j.laar.2014.452.

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In cytogenetics, karyotype analysis is used to assess the presence of genetic defects by visualization chromosomes structure from microscopic images. A key step in this process is image thresholding, used to detect and extract objects of interest from background, as it affects the performance of further processing steps in image analysis. In this paper, an adaptive local thresholding for Qband chromosome image segmentation is presented. A re-threshold process based on the Sauvola’s local adaptive technique is applied to extract chromosomes from background. Local adaptive histogram equalization

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Jasim, Wala’a, and Rana Mohammed. "A Survey on Segmentation Techniques for Image Processing." Iraqi Journal for Electrical and Electronic Engineering 17, no. 2 (2021): 73–93. http://dx.doi.org/10.37917/ijeee.17.2.10.

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The segmentation methods for image processing are studied in the presented work. Image segmentation can be defined as a vital step in digital image processing. Also, it is used in various applications including object co-segmentation, recognition tasks, medical imaging, content based image retrieval, object detection, machine vision and video surveillance. A lot of approaches were created for image segmentation. In addition, the main goal of segmentation is to facilitate and alter the image representation into something which is more important and simply to be analyzed. The approaches of image

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Senthilkumaran, N. "IMAGE SEGMENTATION BY USING THRESHOLDING TECHNIQUES FOR MEDICAL IMAGES." February 29, 2016. https://doi.org/10.5281/zenodo.1197005.

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<strong>ABSTRACT </strong> Image binarization is the process of separation of pixel values into two groups, black as background and white as foreground. Thresholding can be categorized into global thresholding and local thresholding. This paper describes a locally adaptive thresholding technique that removes background by using local mean and standard deviation. Most common and simplest approach to segment an image is using thresholding. In this work we present an efficient implementation for threshoding and give a detailed comparison of Niblack and sauvola local thresholding algorithm. Niblac

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Kim, Moon, Robert Seifert, Jana Fragemann, et al. "Evaluation of thresholding methods for the quantification of [68Ga]Ga-PSMA-11 PET molecular tumor volume and their effect on survival prediction in patients with advanced prostate cancer undergoing [177Lu]Lu-PSMA-617 radioligand therapy." European Journal of Nuclear Medicine and Molecular Imaging, March 2, 2023. http://dx.doi.org/10.1007/s00259-023-06163-x.

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Abstract Purpose The aim of this study was to systematically evaluate the effect of thresholding algorithms used in computer vision for the quantification of prostate-specific membrane antigen positron emission tomography (PET) derived tumor volume (PSMA-TV) in patients with advanced prostate cancer. The results were validated with respect to the prognostication of overall survival in patients with advanced-stage prostate cancer. Materials and methods A total of 78 patients who underwent [177Lu]Lu-PSMA-617 radionuclide therapy from January 2018 to December 2020 were retrospectively included in

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Erwin, Hadrians Kesuma Putra, Bambang Suprihatin, and Fathoni. "Retinal Blood Vessel Extraction Using a New Enhancement Technique of Modified Convolution Filters and Sauvola Thresholding." International Journal of Image and Graphics, December 10, 2021. http://dx.doi.org/10.1142/s0219467823500067.

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The retinal blood vessels in humans are major components with different shapes and sizes. The extraction of the blood vessels from the retina is an important step to identify the type or nature of the pattern of the diseases in the retina. Furthermore, the retinal blood vessel was also used for diagnosis, detection, and classification. The most recent solution in this topic is to enable retinal image improvement or enhancement by a convolution filter and Sauvola threshold. In image enhancement, gamma correction is applied before filtering the retinal fundus. After that, the image should be tra

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Sukanthi, S. Sakthivel Murugan, and S. Hanis. "Binarization of Stone Inscription Images by Modified Bi-level Entropy Thresholding." Fluctuation and Noise Letters, May 4, 2021, 2150054. http://dx.doi.org/10.1142/s0219477521500541.

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India is rich in its heritage and culture. It has many historical monuments and temples where the walls are made of inscribed stones and rocks. The stone inscriptions play a vital role in portraying about the ancient incidents. Hence, the digitization of these stone inscriptions is necessary and contributes much for the epigraphers. Recently, the digitizing of these inscriptions began with the binarization process of stone inscriptions. This process mainly depends on the thresholding technique. In this paper, the binarization of terrestrial and underwater stone inscription images is preceded b

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Hafizan, Mat Som. "APPLICATION OF THRESHOLD TECHNIQUES FOR READABILITY IMPROVEMENT OF JAWI HISTORICAL MANUSCRIPT IMAGES." July 11, 2018. https://doi.org/10.5281/zenodo.1309093.

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ABSTRACT:  Problem statement: Historical documents such as old books and manuscripts have a high esthetic value and highly appreciated. Unfortunately, there are some documents cannot be read due to quality problems like faded paper, ink expand, uneven color tone, torn paper and other elements disruption such as the existence of small spots. The study aims to produce a copy of manuscript that shows clear wordings so they can easily be read and the copy can also be displayed for visitors. Approach: 16 samples of Jawi historical manuscript with different quality problems were obtained from T

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Hafizan, Mat Som. "APPLICATION OF THRESHOLD TECHNIQUES FOR READABILITY IMPROVEMENT OF JAWI HISTORICAL MANUSCRIPT IMAGES." July 19, 2018. https://doi.org/10.5281/zenodo.1316909.

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ABSTRACT: Abstract: Problem statement: Historical documents such as old books and manuscripts have a high esthetic value and highly appreciated. Unfortunately, there are some documents cannot be read due to quality problems like faded paper, ink expand, uneven color tone, torn paper and other elements disruption such as the existence of small spots. The study aims to produce a copy of manuscript that shows clear wordings so they can easily be read and the copy can also be displayed for visitors. Approach: 16 samples of Jawi historical manuscript with different quality problems were obtained fr

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Patil, Mangesh S. Dudhgaonkar, and Sudeep D. Thepade. "Improved classification of histopathological images with feature fusion of Thepade SBTC and Sauvola thresholding using machine learning." International Journal of Computational Vision and Robotics 1, no. 1 (2023). http://dx.doi.org/10.1504/ijcvr.2023.10058302.

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H. Dewan, Jaya, and Sudeep D. Thepade. "Image Retrieval Using Fusion of Sauvola and Thepade’s Sorted Block Truncation Coding-Based Color Features." Pertanika Journal of Science and Technology 31, no. 5 (2023). http://dx.doi.org/10.47836/pjst.31.5.06.

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Because of the tremendous growth in digital imaging, enhanced communication and storage technology, billions of images are captured, stored, and exchanged daily. Finding and searching for an image in a large collection is becoming challenging. The query by reference image retrieval (IR) technique aims to close the semantic gap between the query and retrieve images while improving performance. The primary goal of the work proposed here is to develop discriminative and descriptive features of the image with the minimum possible size. Here, the weighted feature fusion-based IR technique is propos

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Muchallil, Sayed, Fitri Arnia, Khairul Munadi, and Fardian Fardian. "PERFORMANCE COMPARISON OF DENOISING METHODS FOR HISTORICAL DOCUMENTS." Jurnal Teknologi 77, no. 22 (2015). http://dx.doi.org/10.11113/jt.v77.6676.

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Image denoising plays an important role in image processing. It is also part of the pre-processing technique in a binarization complete procedure that consists of pre-processing, thresholding, and post-processing. Our previous research has confirmed that the Discrete Cosine Transform (DCT)-based filtering as the new pre-processing process improved the performance of binarization output in terms of recall and precision. This research compares three classical denoising methods; Gaussian, mean, and median filtering with the DCT-based filtering. The noisy ancient document images are filtered using

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Thepade, Sudeep D., and Piyush R. Chaudhari. "Land Usage Identification with Fusion of Thepade SBTC and Sauvola Thresholding Features of Aerial Images Using Ensemble of Machine Learning Algorithms." Applied Artificial Intelligence, November 5, 2020, 1–17. http://dx.doi.org/10.1080/08839514.2020.1842627.

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Jyothi, R. L., and M. Abdul Rahiman. "Document image binarization using difference of concatenated convolutions." Journal of Intelligent & Fuzzy Systems, August 7, 2021, 1–14. http://dx.doi.org/10.3233/jifs-210015.

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Binarization is the most important stage in historical document image processing. Efficient working of character and word recognition algorithms depend on effective segmentation methods. Segmentation algorithms in turn depend on images free of noises and degradations. Most of these historical documents are illegible with degradations like bleeding through degradation, faded ink or faint characters, uneven illumination, contrast variation, etc. For effective processing of these document images, efficient binarization algorithms should be devised. Here a simple modified version of the Convolutio

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Fu, Daixin, Bowen Kuang, Lin Mi, et al. "A threshold-based prompt generation method for segment anything model to identify fission gas bubbles." International Journal of Structural Integrity, June 3, 2025. https://doi.org/10.1108/ijsi-03-2025-0059.

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PurposeThis study addresses the computational and accuracy limitations of the Segment Anything Model (SAM) by Meta AI in segmenting microscopic pores on irradiated nuclear fuel surfaces. It proposes an optimized framework combining adaptive prompts, boundary enhancement, and lightweight SAM variants to automate defect analysis—critical for evaluating nuclear fuel structural integrity and safety.Design/methodology/approachA three-stage approach improved SAM: (1) Sauvola-based adaptive thresholding for optimizing prompt ratios (2:1 positive/negative); (2) Gradient filtering to sharpen pore bound

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Sharma, Neenu, and Ramesh Kumar Sunkaria. "Improved T-wave detection in electrocardiogram signals based non-stationary wavelet transform and QRS complex cancellation with kurtosis analysis." Physiological Measurement, November 9, 2023. http://dx.doi.org/10.1088/1361-6579/ad0b3e.

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Abstract Abstract: Objective: The T-wave in electrocardiogram (ECG) signal has the potential to enumerate various cardiac dysfunctions in the cardiovascular system. The primary objective of this research is to develop an efficient method for detecting T-waves in ECG signals, with potential applications in clinical diagnosis and continuous patient monitoring. &#xD;Approach: In this work, we propose a novel algorithm for T-wave peak detection, which relies on a Non-decimated stationary wavelet transform method (NSWT) and involves the cancellation of the QRS complex by utilizing its local ext

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Malik, Reza Firsandaya, Saparudin, and Intan Septyliana. "An Analysis of Adaptive Approach for Document Binarization." Computer Engineering and Applications Journal 2, no. 2 (2013). http://dx.doi.org/10.18495/comengapp.v2i2.21.

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Abstract Binarization is an initial step in document image analysis for differentiate text area from background. Determination of binarization technique is really important to retrieve all the text information especially from degraded document image. This paper explains about adaptive binarization using Gatosâ€™s method. Gatosâ€™s method is doing preprocessing, foreground estimation using Sauvolaâ€™s method, background estimation, upsampling, final thresholding and postprocessing. In this paper, Sauvolaâ€™s method is final thresholding from Wiener filter image result and source image, and coun

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Maheswari, S. Uma, P. Uma Maheswari, and G. R. Sai Aakaash. "An intelligent character segmentation system coupled with deep learning based recognition for the digitization of ancient Tamil palm leaf manuscripts." Heritage Science 12, no. 1 (2024). http://dx.doi.org/10.1186/s40494-024-01438-4.

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AbstractPalm-leaf manuscripts, rich with ancient knowledge in areas such as history, art, and medicine, are vital cultural treasures, making their digitization essential for preserving this heritage. Digitization of these organic and fragile manuscripts is required to safeguard the essential ancient data. This requires optimal character segmentation and recognition algorithms. A limited number of studies have been carried out in Tamil character recognition in literature. Handling row-overlapped characters, noise introduced due to lightning issues, and dirt, as well as the removal of punch hole

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