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Статті в журналах з теми "Local adaptive threshold"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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1

Hatta, Moch., and I. Gde Susrama. "COUNTING SPERMA AKTIF MENGGUNAKAN METODE OTSU THRESHOLD DAN LOCAL ADAPTIVE THRESHOLD." Teknika : Engineering and Sains Journal 1, no. 1 (2017): 47–54. https://doi.org/10.5281/zenodo.1067713.

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Analisis sperma adalah pemeriksaan awal yang dilakukan pada kasus <em>infertilitas</em> pria, salah satunya adalah menentukan <em>motiliti</em> normal dan abnormal, yang dilakukan oleh ahli. Analisa sperma ini juga dapat dilakukan secara otomatis dengan berbantuan komputer, yaitu dengan cara mengambil per-<em>frame</em> video sperma kemudian dilakukan proses segmentasi. Pada proses segmentasi terdapat beberapa kendala antara lain data video yang diambil mempunyai intensitas yang berbeda, sehingga diperlukan beberapa metode segmentasi. Penelitian ini adalah membandingkan proses <em>Otsu Thresho

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2

Hatta, Moch, and I. Gde Susrama. "COUNTING SPERMA AKTIF MENGGUNAKAN METODE OTSU THRESHOLD DAN LOCAL ADAPTIVE THRESHOLD." Teknika: Engineering and Sains Journal 1, no. 1 (2017): 47. http://dx.doi.org/10.51804/tesj.v1i1.68.47-54.

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Analisis sperma adalah pemeriksaan awal yang dilakukan pada kasus infertilitas pria, salah satunya adalah menentukan motiliti normal dan abnormal, yang dilakukan oleh ahli. Analisa sperma ini juga dapat dilakukan secara otomatis dengan berbantuan komputer, yaitu dengan cara mengambil per-frame video sperma kemudian dilakukan proses segmentasi. Pada proses segmentasi terdapat beberapa kendala antara lain data video yang diambil mempunyai intensitas yang berbeda, sehingga diperlukan beberapa metode segmentasi. Penelitian ini adalah membandingkan proses Otsu Threshold dan proses Local Adaptive Th

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3

Hua, Man, Yan Ling Li, and Rui Chun Lin. "An Adaptive Moving Objects Detection Algorithm Based on Kernel Density Estimation." Applied Mechanics and Materials 475-476 (December 2013): 983–86. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.983.

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The detection of moving objects are important research area for video surveillance and other video processing applications. In this paper, we propose an adaptive approach modeling background and segmenting moving object with non-parametric kernel density estimation. Unlike previous approaches to object detection which detect objects by global threshold, we use a local threshold to reflect temporal persistence. With combined of global threshold and local thresholds, the proposed approach can handle scenes containing gradual illumination variations and noise and has no bootstrapping limitations.

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4

Bao, Q. Z., J. H. Gao, and W. C. Chen. "Local adaptive shrinkage threshold denoising using curvelet coefficients." Electronics Letters 44, no. 4 (2008): 277. http://dx.doi.org/10.1049/el:20082831.

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5

WANG, Yin, Zheng JIANG, and Bin LIU. "SIFT fast image matching algorithm with local adaptive threshold." Chinese Journal of Liquid Crystals and Displays 39, no. 2 (2024): 228–36. http://dx.doi.org/10.37188/cjlcd.2023-0085.

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6

Hua, Man, Yanling Li, and Yinhui Luo. "Robust Background Modeling with Kernel Density Estimation." International Journal of Online Engineering (iJOE) 11, no. 8 (2015): 13. http://dx.doi.org/10.3991/ijoe.v11i8.4880.

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Modeling background and segmenting moving objects are significant techniques for video surveillance and other video processing applications. In this paper, we proposed a novel adaptive approach modeling background and segmenting moving object with non-parametric kernel density estimation. Unlike previous approaches to object detection which detect objects by global threshold, we use a local threshold to reflect temporal persistence. With combined of global threshold and local thresholds, the proposed approach can handle scenes containing gradual illumination variations and noise and has no boo

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7

Damjanović, Sanja, Ferdinand van der Heijden, and Luuk J. Spreeuwers. "Local Stereo Matching Using Adaptive Local Segmentation." ISRN Machine Vision 2012 (August 23, 2012): 1–11. http://dx.doi.org/10.5402/2012/163285.

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We propose a new dense local stereo matching framework for gray-level images based on an adaptive local segmentation using a dynamic threshold. We define a new validity domain of the frontoparallel assumption based on the local intensity variations in the 4 neighborhoods of the matching pixel. The preprocessing step smoothes low-textured areas and sharpens texture edges, whereas the postprocessing step detects and recovers occluded and unreliable disparities. The algorithm achieves high stereo reconstruction quality in regions with uniform intensities as well as in textured regions. The algori

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8

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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9

Liu, Dan, Dajun Li, Meizhen Wang, and Zhiming Wang. "3D Change Detection Using Adaptive Thresholds Based on Local Point Cloud Density." ISPRS International Journal of Geo-Information 10, no. 3 (2021): 127. http://dx.doi.org/10.3390/ijgi10030127.

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In recent years, because of highly developed LiDAR (Light Detection and Ranging) technologies, there has been increasing demand for 3D change detection in urban monitoring, urban model updating, and disaster assessment. In order to improve the effectiveness of 3D change detection based on point clouds, an approach for 3D change detection using point-based comparison is presented in this paper. To avoid density variation in point clouds, adaptive thresholds are calculated through the k-neighboring average distance and the local point cloud density. A series of experiments for quantitative evalu

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10

Muhammad Asif, Rao, Mustafa Shakir, Jamel Nebhen, Ateeq Ur Rehman, Muhammad Shafiq, and Jin-Ghoo Choi. "Defocus Blur Segmentation Using Local Binary Patterns with Adaptive Threshold." Computers, Materials & Continua 71, no. 1 (2022): 1597–611. http://dx.doi.org/10.32604/cmc.2022.022219.

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11

ZHANG, Peixiang, Qi WANG, Renjing GAO, Yang XIA, and Zhenzhong WAN. "Ground point cloud segmentation based on local threshold adaptive method." Optics and Precision Engineering 31, no. 17 (2023): 2564–72. http://dx.doi.org/10.37188/ope.20233117.2564.

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12

Seng Gan, Hong, Bakhtiar Al-Jefri Adb Salam, Aida Syafiqah Ahmad Khaizi, et al. "Local mean based adaptive thresholding to classify the cartilage and background superpixels." Indonesian Journal of Electrical Engineering and Computer Science 15, no. 1 (2019): 211. http://dx.doi.org/10.11591/ijeecs.v15.i1.pp211-220.

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<em><span>Semi-automatic segmentation is common in medical image processing because anatomical geometries demonstrated by human anatomical parts often requires manual supervision to provide desirable results. However, semi-automatic segmentation has been infamous for requiring excessive human intervention and time consuming. In order to reduce a forementioned problems, seed labels have been generated automatically using superpixels in our previous works. A fixed threshold method has been implemented to classify cartilage and background superpixels but this method is reported to lac

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13

Tang, Qi, Wang Haixing, and Liu Qunpo. "Adaptive Threshold and Weighted Frequency Domain Histogram of Local Binary Patterns." Engineering and Technology Journal 9, no. 04 (2024): 3725–30. https://doi.org/10.5281/zenodo.10948874.

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Wire ropes are crucial load-bearing components in mining conveyance equipment, and machine vision is one of the methods used to assess the surface damage condition of wire ropes. In response to the light-sensitive nature of local binary patterns, which leads to issues such as differing feature values for similar textures and susceptibility to the influence of excessively large or small pixels within local windows, hindering the accurate reflection of window structure information and exacerbating the introduction of considerable feature noise, an investigation is conducted. To enhance the gradi

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14

Wang Min, 王民, 刘涛 Liu Tao, and 贠卫国 Yun Weiguo. "Corner Detection Algorithm Based on Local Weighted Entropy and Adaptive Threshold." Laser & Optoelectronics Progress 54, no. 5 (2017): 051003. http://dx.doi.org/10.3788/lop54.051003.

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15

Li, Hang, Hongfan Yang, and Kaiyang Chen. "Feature Point Extraction and Tracking Based on a Local Adaptive Threshold." IEEE Access 8 (2020): 44325–34. http://dx.doi.org/10.1109/access.2020.2977841.

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16

Zuraini, Othman, Abdullah Azizi, Kasmin Fauziah, and Sakinah Syed Ahmad Sharifah. "Road crack detection using adaptive multi resolution thresholding techniques." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 4 (2019): 1874–81. https://doi.org/10.12928/TELKOMNIKA.v17i4.12755.

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Machine vision is very important for ensuring the success of intelligent transportation systems, particularly in the area of road maintenance. For this reason, many studies had been focusing on automatic image-based crack detection as a replacement for manual inspection that had depended on the specialist’s knowledge and expertise. In the image processing technique, the pre-processing and edge detection stages are important for filtering out noises and in enhancing the quality of the edges in the image. Since threshold is one of the powerful methods used in the edge detection of an image

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17

Lv, Yong, Yi Zhang, and Cancan Yi. "Optimized Adaptive Local Iterative Filtering Algorithm Based on Permutation Entropy for Rolling Bearing Fault Diagnosis." Entropy 20, no. 12 (2018): 920. http://dx.doi.org/10.3390/e20120920.

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The characteristics of the early fault signal of the rolling bearing are weak and this leads to difficulties in feature extraction. In order to diagnose and identify the fault feature from the bearing vibration signal, an adaptive local iterative filter decomposition method based on permutation entropy is proposed in this paper. As a new time-frequency analysis method, the adaptive local iterative filtering overcomes two main problems of mode decomposition, comparing traditional methods: modal aliasing and the number of components is uncertain. However, there are still some problems in adaptiv

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18

Bogiatzis, Athanasios, and Basil Papadopoulos. "Global Image Thresholding Adaptive Neuro-Fuzzy Inference System Trained with Fuzzy Inclusion and Entropy Measures." Symmetry 11, no. 2 (2019): 286. http://dx.doi.org/10.3390/sym11020286.

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Thresholding algorithms segment an image into two parts (foreground and background) by producing a binary version of our initial input. It is a complex procedure (due to the distinctive characteristics of each image) which often constitutes the initial step of other image processing or computer vision applications. Global techniques calculate a single threshold for the whole image while local techniques calculate a different threshold for each pixel based on specific attributes of its local area. In some of our previous work, we introduced some specific fuzzy inclusion and entropy measures whi

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19

Kountchev, Roumen, Alexander Bekiarski, Rumen Mironov, and Snezhana Pleshkova. "A Method for Local Contrast Enhancement of Endoscopic Images Based on Color Tensor Transformation into a Matrix of Color Vectors’ Modules Using a Sliding Window." Symmetry 14, no. 12 (2022): 2582. http://dx.doi.org/10.3390/sym14122582.

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A new method aimed at endoscopic color images’ local contrast enhancement is proposed, based on local sliding histogram equalization with adaptive threshold limitation, color distortions correction, and image brightness preservation. For this, the original RGB image, represented as a tensor of size M × N × 3, is transformed into a matrix of size M × N, composed by the color vectors’ modules. As a result of local contrast enhancement, the obtained color vectors are symmetrical in respect of the input ones, because they satisfy the requirement for invariance after rotation. To enhance the local

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20

Zhao, Hongyang, and Miaoyi Shang. "An adaptive edge-detection method based on histogram." Modern Physics Letters B 32, no. 34n36 (2018): 1840088. http://dx.doi.org/10.1142/s0217984918400882.

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In order to solve the problems of poor adaptability when setting threshold and the high probability of detecting pseudo-edges in the existing methods of edge detection, the paper proposes an adaptive edge-detection method based on histogram. Multi-scale wavelet transform is used to preprocess the image, the image details are highlighted obviously, and it also can avoid the effect of manual setting filter coefficients. Difference of gray values between the pixels of local area are used to calculate the gradients comprehensively, it extends the gradient direction to four directions. When calcula

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21

Cao Hongyan, 曹红燕, 刘长明 Liu Changming, 沈小林 Shen Xiaolin, 李大威 Li Dawei, and 陈燕 Chen Yan. "Low Illumination Image Processing Based on Adaptive Threshold and Local Tone Mapping." Laser & Optoelectronics Progress 58, no. 4 (2021): 0410017. http://dx.doi.org/10.3788/lop202158.0410017.

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22

Zhang, Yuhan, Xi Wang, Haishu Tan, Chang Xu, Xu Ma, and Tingfa Xu. "Region Merging Method for Remote Sensing Spectral Image Aided by Inter-Segment and Boundary Homogeneities." Remote Sensing 11, no. 12 (2019): 1414. http://dx.doi.org/10.3390/rs11121414.

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Image segmentation is extensively used in remote sensing spectral image processing. Most of the existing region merging methods assess the heterogeneity or homogeneity using global or pre-defined parameters, which lack the flexibility to further improve the goodness-of-fit. Recently, the local spectral angle (SA) threshold was used to produce promising segmentation results. However, this method falls short of considering the inherent relationship between adjacent segments. In order to overcome this limitation, an adaptive SA thresholds methods, which combines the inter-segment and boundary hom

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23

Chai, Ruishuai. "Otsu’s Image Segmentation Algorithm with Memory-Based Fruit Fly Optimization Algorithm." Complexity 2021 (March 25, 2021): 1–11. http://dx.doi.org/10.1155/2021/5564690.

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In this paper, the most common pepper noise in grayscale image noise is investigated in depth in the median filtering algorithm, and the improved median filtering algorithm, adaptive switching median filtering algorithm, and adaptive polar median filtering algorithm are applied to the OTSU algorithm. Two improved OTSU algorithms such as the adaptive switched median filter-based OTSU algorithm and the polar adaptive median filter-based OTSU algorithm are obtained. The experimental results show that the algorithm can better cope with grayscale images contaminated by pretzel noise, and the segmen

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24

Parsai, Soroosh, and Majid Ahmadi. "New Local Binary Pattern Feature Extractor with Adaptive Threshold for Face Recognition Applications." International Journal of Artificial Intelligence & Applications 13, no. 4 (2022): 79–87. http://dx.doi.org/10.5121/ijaia.2022.13406.

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This paper represents a feature extraction method constructed on the local binary pattern (LBP) structure. The proposed method introduces a new adaptive thresholding function to the LBP method replacing the fixed thresholding at zero. The introduced function is a Gaussian Distribution Function (GDF) variation. The proposed technique uses the global and local information of the image and image blocks to perform the adaptation. The adaptive function adds to the on-hand im-age’s features by preserving the information of the amplitude of the pixel difference rather than just considering the sign o

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25

Xiang, Liang, Xiajie Zhao, Jianfeng Wang, and Bin Wang. "An Enhanced Human Evolutionary Optimization Algorithm for Global Optimization and Multi-Threshold Image Segmentation." Biomimetics 10, no. 5 (2025): 282. https://doi.org/10.3390/biomimetics10050282.

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Thresholding image segmentation aims to divide an image into a number of regions with different feature attributes in order to facilitate the extraction of image features in the context of image detection and pattern recognition. However, existing threshold image-segmentation methods suffer from the problem of easily falling into locally optimal thresholds, resulting in poor image segmentation. In order to improve the image-segmentation performance, this study proposes an enhanced Human Evolutionary Optimization Algorithm (HEOA), known as CLNBHEOA, which incorporates Otsu’s method as an object

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26

Wang, Zhichong, Tao Chen, Xudong Lin, Liang Wang, Qichang An, and Jintian Hu. "A Local Threshold Checkerboard Algorithm for Adaptive Optics System With a Plenoptic Sensor." IEEE Photonics Journal 14, no. 1 (2022): 1–9. http://dx.doi.org/10.1109/jphot.2021.3138776.

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27

Ji, Shi, Tianlu Xi, and Xingchen Fan. "High-Definition Garden Plant Images Threshold Segmentation Mechanism Based on PSO and DRL." International Journal of Swarm Intelligence Research 15, no. 1 (2024): 1–17. http://dx.doi.org/10.4018/ijsir.348970.

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The accuracy of the threshold determines the quality of high-definition garden plant image segmentation. How to accurately and quickly search for the best combination of multiple thresholds is currently a research difficulty. In this regard, this article proposes an improved adaptive particle swarm optimization algorithm with extremal disturbance (IAPSO), which can to some extent prevent the PSO from falling into local optima by implementing extreme perturbation strategies. Then, by combining IAPSO and Deep Reinforcement Learning (DRL), the IAPSO-RL based on policy gradient off policy is propo

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28

Liang, Xin He, Jin Liang, and Chen Guo. "Scatter Point Cloud Denoising Based on Self-Adaptive Optimal Neighborhood." Advanced Materials Research 97-101 (March 2010): 3631–36. http://dx.doi.org/10.4028/www.scientific.net/amr.97-101.3631.

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We present a scatter point cloud denoising method, which can reduce noise effectively, while preserving mesh features such as sharp edges and corners. The method consists of two stages. Firstly, noisy points normal are filtered iteratively; second, location noises of points are reduced. How to select proper denoising neighbors is a key problem for scatter point cloud denoising operation. The local shape factor which related to the surface feature is proposed. By using the factor, we achieved the shape adaptive angle threshold and adaptive optimal denoising neighbor. Normal space and location s

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29

Lv, Peng-Fei, and Yan-Qing Hong. "Self-Pilot Tone Based Adaptive Threshold RZ-OOK Decision for Free-Space Optical Communications." Photonics 10, no. 7 (2023): 714. http://dx.doi.org/10.3390/photonics10070714.

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This paper studies a novel self-pilot tone based adaptive threshold return-to-zero on-off keying (RZ-OOK) decision for free-space optical (FSO) communications. RZ-OOK has the characteristics of impulse series in the spectrum. Therefore, these impulses can be utilized as the pilot tones of the transmitted signal to convey the channel state information (CSI) of FSO links. Then, the CSI signal is extracted using a local oscillator (LO) with the frequencies of the impulse series and low pass filter. Finally, the adaptive threshold decision (ATD) is realized by assigning optimized weight factors in

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30

Chu, Guoming, Yan Peng, and Xuhong Luo. "ALGD-ORB: An improved image feature extraction algorithm with adaptive threshold and local gray difference." PLOS ONE 18, no. 10 (2023): e0293111. http://dx.doi.org/10.1371/journal.pone.0293111.

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Simultaneous Localization and Mapping (SLAM) technology is crucial for achieving spatial localization and autonomous navigation. Finding image features that are representative presents a key challenge in visual SLAM systems. The widely used ORB (Oriented FAST and Rotating BRIEF) algorithm achieves rapid image feature extraction. However, traditional ORB algorithms face issues such as dense, overlapping feature points, and imbalanced distribution, resulting in mismatches and redundancies. This paper introduces an image feature extraction algorithm called Adaptive Threshold and Local Gray Differ

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31

Xu, Jin, Haixia Wang, Can Cui, Baigang Zhao, and Bo Li. "Oil Spill Monitoring of Shipborne Radar Image Features Using SVM and Local Adaptive Threshold." Algorithms 13, no. 3 (2020): 69. http://dx.doi.org/10.3390/a13030069.

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In the case of marine accidents, monitoring marine oil spills can provide an important basis for identifying liabilities and assessing the damage. Shipborne radar can ensure large-scale, real-time monitoring, in all weather, with high-resolution. It therefore has the potential for broad applications in oil spill monitoring. Considering the original gray-scale image from the shipborne radar acquired in the case of the Dalian 7.16 oil spill accident, a complete oil spill detection method is proposed. Firstly, the co-frequency interferences and speckles in the original image are eliminated by pre

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32

He, Yang Ming, and Jian Qiang Du. "Application of Improved BP Neural Network in Threshold Selection for Image Processing." Advanced Materials Research 860-863 (December 2013): 2872–75. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2872.

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There are a lot of methods to select threshold in image processing. Because BP neural network can adapt to fixed environment, it is applied in this area in this paper. Firstly, according to the feature of image, BP neural network is constructed. The input items of network are the features of image. The mean value and variance of gray in the image is the important features of image, so two input items can be chosen. The output items are the values of threshold. If one threshold is chosen, one output item can be chosen. In some condition, two thresholds should be set, then two output items would

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33

Dong, Ting Jian, Hua Peng Ding, Tao Wang, Hao Wang, and Jin Chen. "Adaptive Denoising Algorithm for Scanning Beam Points Based on Angle Thresholds." Applied Mechanics and Materials 741 (March 2015): 204–8. http://dx.doi.org/10.4028/www.scientific.net/amm.741.204.

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A local adaptive neighborhood model is proposed in this paper in order to deal with the mistake judgment in the existing scanning beam point cloud denoising algorithms. Such a model regards larger curvatures as the potential noises, can select angle thresholds of noise points and the median values of filtering windows adaptively, so as address the issues of mistake judgment and missing judgment of the point clouds denoising algorithms with different curvatures. The adaption theory in the angle threshold denoising algorithm classifies the noise points and data points. Therefore, it can ensure t

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34

Chai, J. X., Y. S. Zhang, Z. Yang, and J. Wu. "3D CHANGE DETECTION OF POINT CLOUDS BASED ON DENSITY ADAPTIVE LOCAL EUCLIDEAN DISTANCE." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2022 (May 30, 2022): 523–30. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2022-523-2022.

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Abstract. With the development of sensors and multi-view stereo matching technology, image-based dense matching point cloud data shares higher geometric accuracy and richer spectral information, and such data is therefore widely used in change detection-related research. Due to the inconsistent position and attitude of the image acquisition for generating two phases of point clouds, as well as the seasonal variation of vegetation, the 3D change detection is often subject to false detection. To improve the accuracy of 3D change detection of point clouds in large fields, a method of 3D change de

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35

Liu, Yuanhua, and Meiling Zhang. "Hard-Decision Bit-Flipping Decoder Based on Adaptive Bit-Local Threshold for LDPC Codes." IEEE Communications Letters 23, no. 5 (2019): 789–92. http://dx.doi.org/10.1109/lcomm.2019.2909207.

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36

Sun, Hongfei, Jianhua Yang, Rongbo Fan, Kai Xie, Conghui Wang, and Xinye Ni. "Stepwise local stitching ultrasound image algorithms based on adaptive iterative threshold Harris corner features." Medicine 99, no. 37 (2020): e22189. http://dx.doi.org/10.1097/md.0000000000022189.

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37

Guo, Jing-Ming, Li-Ying Chang, and Jiann-Der Lee. "An Efficient and Geometric-Distortion-Free Binary Robust Local Feature." Sensors 19, no. 10 (2019): 2315. http://dx.doi.org/10.3390/s19102315.

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An efficient and geometric-distortion-free approach, namely the fast binary robust local feature (FBRLF), is proposed. The FBRLF searches the stable features from an image with the proposed multiscale adaptive and generic corner detection based on the accelerated segment test (MAGAST) to yield an optimum threshold value based on adaptive and generic corner detection based on the accelerated segment test (AGAST). To overcome the problem of image noise, the Gaussian template is applied, which is efficiently boosted by the adoption of an integral image. The feature matching is conducted by incorp

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38

Pambudi, Elindra Ambar, and Muhammad Ivan Nurhidayat. "Impact of Wolf Thresholding on Background Subtraction for Human Motion Detection." Compiler 13, no. 1 (2024): 39. http://dx.doi.org/10.28989/compiler.v13i1.2116.

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Series of motion detection based on background subtraction there is an image segmentation stage. Thresholding is a common technique used for the segmentation process. There are two types that can be used in thresholding techniques namely local and global. This research intends to implement local adaptive wolf thresholding as the threshold value of the background subtraction method to detect motion objects. The proposed method consists of the reading frame, background and foreground initialization of each frame, preprocessing, background subtraction, wolf thresholding, providing a bounding box,

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39

Sun, Tao, and Chang Zhi Gao. "An Improved Canny Edge Detection Algorithm." Applied Mechanics and Materials 291-294 (February 2013): 2869–73. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2869.

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Traditional Canny edge detection algorithm uses a global threshold selection method, when large changes are in the background of the image and the target gray, global threshold method may lose some local edge information. For this problem, this paper therefore proposes an adaptive dynamic threshold improved Canny edge detection algorithm. The method uses image gradient variance as the criterion of the image block according to the four forks tree principle, then uses the Otsu method to get the corresponding sub-block threshold value for each sub-block, and obtains threshold value matrix by inte

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40

Abrahim, Araz R., Mohd Sh Mohd Rahim, and Ahmed S. Sami. "Image Splicing Forgery Detection Scheme Using New Local Binary Pattern Varient." Academic Journal of Nawroz University 9, no. 3 (2020): 208. http://dx.doi.org/10.25007/ajnu.v9n3a780.

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In this research develop passive image splicing detection method based on a new descriptor called Adaptive Threshold Mean Ternary Pattern (ATMTP). It was developed based on strength and weaknesses of both Local Binary Pattern (LBP) and Local Ternary Pattern (LTP). ATMTP extraction feature is normally achieved by using proposed mean based thresholding and adaptive ternary thresholding, the former is robust to noise while the latter is robust to noise and other photometric attacks. It is designed to withstand against photometric manipulations, be it single or double attacks. In this research the

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41

Wu, Liangcheng, Kai Lin, Xiaoyu Lin, and Juan Lin. "List-Based Threshold Accepting Algorithm with Improved Neighbor Operator for 0–1 Knapsack Problem." Algorithms 17, no. 11 (2024): 478. http://dx.doi.org/10.3390/a17110478.

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The list-based threshold accepting (LBTA) algorithm is a sophisticated local search method that utilizes a threshold list to streamline the parameter tuning process in the traditional threshold accepting (TA) algorithm. This paper proposes an enhanced local search version of the LBTA algorithm specifically tailored for solving the 0–1 knapsack problem (0–1 KP). To maintain a dynamic threshold list, a feasible threshold updating strategy is designed to accept adaptive modifications during the search process. In addition, the algorithm incorporates an improved bit-flip operator designed to gener

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42

Zhang Zhipeng, 张志鹏, 刘鑫 Liu Xin, 施韬 Shi Tao, 王尔申 Wang Ershen та 何宽 He Kuan. "基于自适应局部滤波阈值的城郊地区点云滤波算法". Laser & Optoelectronics Progress 62, № 2 (2025): 0215003. https://doi.org/10.3788/lop240913.

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43

Cheng, Diancheng, Fan Wu, Cong Zhang, and Yuan’an Liu. "Adaptive Multi-Source Ambient Backscatter Communication Technique for Massive Internet of Things." Electronics 14, no. 8 (2025): 1532. https://doi.org/10.3390/electronics14081532.

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Ambient backscatter communication (AmBC) has been regarded as an energy- and spectrum-efficient backscatter scheme for the massive Internet of Things (IoT). However, most existing AmBC systems are non-adaptive end-to-end systems, which cannot fully accommodate the forthcoming massive communications of the sixth-generation (6G) wireless communication systems. Adaptive backscatter communication has emerged as a research hotspot in AmBC in recent years. In this paper, we propose a novel adaptive backscatter technique on passive backscatter devices (BDs) in massive IoT scenarios. We first design a

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44

Yan, Liping, Haoliang Feng, Benyong Chen, Xinyong Tang, and Liu Huang. "Adaptive local threshold segmentation for Fourier spatial filtering in automatic analysis of digital speckle interferogram." Optical Engineering 59, no. 04 (2020): 1. http://dx.doi.org/10.1117/1.oe.59.4.046108.

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45

Burghardt, Andrew J., Galateia J. Kazakia, and Sharmila Majumdar. "A Local Adaptive Threshold Strategy for High Resolution Peripheral Quantitative Computed Tomography of Trabecular Bone." Annals of Biomedical Engineering 35, no. 10 (2007): 1678–86. http://dx.doi.org/10.1007/s10439-007-9344-4.

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46

Andreatos, Antonios, and Apostolos Leros. "Contour Extraction Based on Adaptive Thresholding in Sonar Images." Information 12, no. 9 (2021): 354. http://dx.doi.org/10.3390/info12090354.

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A common problem in underwater side-scan sonar images is the acoustic shadow generated by the beam. Apart from that, there are a number of reasons impairing image quality. In this paper, an innovative algorithm improving contour extraction is presented. Contour extraction is based on automatically estimating the optimal threshold for converting the original gray scale images into binary images. The proposed algorithm clears the shadows and masks most of the impairments in side-scan sonar images. The idea is to select a proper threshold towards the rightmost local minimum of the histogram, i.e.

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47

Zhang, Ming Jun, and Xing Qi Yuan. "Study on Filtering Algorithm of Image Using Matlab." Applied Mechanics and Materials 239-240 (December 2012): 1173–78. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1173.

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To increase signal to noise ratio (SNR) and to stress on expectation characters, an improved adaptive minutia preserving smoothing algorithm is proposed using Matlab based on multi-scale and multidirectional masks. This algorithm keeps the mask’s good performance in preserving details. It divides image into sub-images according to the statistics from image gradation-gradient histogram, and the adaptive threshold value generate according to the gradient information of the whole and the local image. This method deals with the difficulty of choosing threshold and improves the automation of image

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48

WANG, Gong, Mingyang SUN, Huiyang SUN, Ye ZHANG, and Ziming TENG. "An adaptive threshold of remaining energy based ant colony routing algorithm." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 40, no. 2 (2022): 442–49. http://dx.doi.org/10.1051/jnwpu/20224020442.

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Because the node energy distribution among wireless sensor networks is not balanced and their routing algorithm is trapped in local optimal solution, this paper proposes the ant colony routing algorithm for wireless sensor network based on the adaptive residual energy threshold (ATRE-ARA). It introduces the search angle correction pheromone heuristic function to limit the search path and to reduce node energy costs. The residual energy threshold of the node is adaptive; the formula of pheromone increment is improved. The upper and lower limits of pheromone concentration are set; the pheromone

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49

KHASHMAN, ADNAN, and BORAN SEKEROGLU. "DOCUMENT IMAGE BINARISATION USING A SUPERVISED NEURAL NETWORK." International Journal of Neural Systems 18, no. 05 (2008): 405–18. http://dx.doi.org/10.1142/s0129065708001671.

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Advances in digital technologies have allowed us to generate more images than ever. Images of scanned documents are examples of these images that form a vital part in digital libraries and archives. Scanned degraded documents contain background noise and varying contrast and illumination, therefore, document image binarisation must be performed in order to separate foreground from background layers. Image binarisation is performed using either local adaptive thresholding or global thresholding; with local thresholding being generally considered as more successful. This paper presents a novel m

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50

Peng, Gui Hua, He Chen, and Qiang Wu. "Infrared Small Target Detection under Complex Background." Advanced Materials Research 346 (September 2011): 615–19. http://dx.doi.org/10.4028/www.scientific.net/amr.346.615.

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This paper presents an algorithm for detecting the small infrared target under complex background. An method, Local Mutation Weighted Information Entropy (LMWIE), is proposed to suppress background. Then, enhance targets’ gray value by calculating the local energy. For the problem that the gray value of noises is enhanced with the gray value improvement of targets, image segmentation bases on the adaptive threshold. Experiment results indicate that it is a robust and effective small target detection algorithm.

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