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Journal articles on the topic 'Zhang-suen algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Ali, Itemad. "Neural Net Approach For Image Thinning." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 2 (October 21, 2021): 66–78. http://dx.doi.org/10.55562/jrucs.v28i2.391.

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Thinning is the operation that seeks to reduce a connected region of pixels of a given property set to a small size. One of the most applications of thinning is the image recognission. In this paper, we proposed a new algorithm for thinning an image using Neural Net approach called (Thinning Back- propagation algorithm, TBP), the results show that the operation considered including Zhang Suen algorithm, Hilditch's algorithm. Applying Zhang Suen and Hilditch's algorithms showed that the output of the Hilditch's algorithm is better from the presence of shape accuracy point of view. The proposed

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Mamatov, Narzullo, Malika Jalelova, Vohid Fayziev, Abdurashid Samijonov, and Boymirzo Samijonov. "Hybrid quadratic diagonal algorithm for thinning contour lines." EPJ Web of Conferences 321 (2025): 03005. https://doi.org/10.1051/epjconf/202532103005.

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One of the main issues of image analysis is the separation of contour lines. Nowadays, many effective methods for dividing contour lines have been developed. In solving some practical problems, the results obtained by contour separation methods will not be enough, that is, operations such as thinning, filling, and smoothing of contour lines are required. In this case, the development of an efficient contour thinning algorithm used for accurate separation of the shape of the object is an urgent issue. Contour thinning algorithms can reduce the amount of data to be processed and increase process

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3

Ma, J. ,., V. Yu Tsviatkou, and V. K. Kanapelka. "Two-step skeletization of binary images based on the Zhang-Suen model and the producing mask." «System analysis and applied information science», no. 1 (April 26, 2021): 62–69. http://dx.doi.org/10.21122/2309-4923-2021-1-62-69.

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The aim of the work is to limit excessive thinning and increase the resistance to contour noise of skeletons resulted from arbitrary binary image shape while maintaining a high skeletonization rate. The skeleton is a set of thin lines, the relative position, the size and shape, which conveys information of size, shape and orientation in space of the corresponding homogeneous region of the image. To ensure resistance to contour noise, skeletonization algorithms are built on the basis of several steps. Zhang-Suen algorithm is widely known by high-quality skeletons and average performance, which

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4

Luthra, Ritika, and Gulshan Goyal. "Simulation of Zhang Suen Algorithm using Feed- Forward Neural Networks." Communications on Applied Electronics 2, no. 5 (2015): 9–15. http://dx.doi.org/10.5120/cae2015651750.

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Malik, Simrat Kaur, and Amrit Kaur. "To Propose an Improvement in Zhang-Suen Algorithm using Genetic Algorithm for Image Thinning." International Journal of Computer & Organization Trends 34, no. 2 (2016): 45–49. http://dx.doi.org/10.14445/22492593/ijcot-v34p312.

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Ouadid, Y., B. Elbalaoui, M. Boutaounte, M. Fakir, and B. Minaoui. "Handwritten tifinagh character recognition using simple geometric shapes and graphs." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 2 (2019): 598–605. https://doi.org/10.11591/ijeecs.v13.i2.pp598-605.

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In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.

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7

Patel, Ronak B., Dilendra Hiran, and Jayesh M. Patel. "Fingerprint Image Thinning by applying Zhang Suen Algorithm on Enhanced Fingerprint Image." International Journal of Computer Sciences and Engineering 7, no. 5 (2019): 1209–14. http://dx.doi.org/10.26438/ijcse/v7i5.12091214.

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Ouadid, Youssef, Abderrahmane Elbalaoui, Mehdi Boutaounte, Mohamed Fakir, and Brahim Minaoui. "Handwritten tifinagh character recognition using simple geometric shapes and graphs." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 2 (2019): 598. http://dx.doi.org/10.11591/ijeecs.v13.i2.pp598-605.

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<p>In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.</p>

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9

Rahayu, Annisa. "Analisa dan Implementasi Metode Zhang-Suen Dalam Pengerangkaan (Skeleton) Pada Citra Untuk Mengurangi Redundant." JURIKOM (Jurnal Riset Komputer) 7, no. 1 (2020): 156. http://dx.doi.org/10.30865/jurikom.v7i1.1946.

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Zhang-Suen is an algorithm for the process of framing an image. This process is often applied to pre-thinning, for example, the initial stages in the pattern recognition process. This is implemented by changing the initial image with binary patterns to represent the framework. In a line-shaped image, the skeleton shows all the information from the original object. The components of the skeleton, namely the position, orientation, and length of the skeleton line segments represent the lines that form the image. These components make it easy to characterize the components of the image. In a line-

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10

J., Shiny Priyadarshini, and Gladis D. "Analogizing the Thinning Algorithm and Elicitation of Vascular Landmark in Retinal Images." International Journal of Cognitive Informatics and Natural Intelligence 10, no. 3 (2016): 29–37. http://dx.doi.org/10.4018/ijcini.2016070103.

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The retinal tissue is composed of network of blood vessels forming a unique biometric pattern. Feature extraction in retinal blood vessel is becoming an emerging trend in the field of personal identification. Because of its unique identity and less vulnerability to noise and distortion it has become one of the most secured biometric identities. The paper highlights the segmentation of blood vessel and the extraction of feature points such as termination and bifurcation points using Zhang Suen's thinning algorithm in retinal images. A comparison has been made and results are analyzed and tabula

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Tong, Siyuan, Yang Yue, Wenbin Li, Yaxiong Wang, Feng Kang, and Chao Feng. "Branch Identification and Junction Points Location for Apple Trees Based on Deep Learning." Remote Sensing 14, no. 18 (2022): 4495. http://dx.doi.org/10.3390/rs14184495.

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Branch identification is key to the robotic pruning system for apple trees. High identification accuracy and the positioning of junction points between branch and trunk are important prerequisites for pruning with a robotic arm. Recently, with the development of deep learning, Transformer has been gradually applied to the field of computer vision and achieved good results. However, the effect of branch identification based on Transformer has not been verified so far. Taking Swin-T and Resnet50 as a backbone, this study detected and segmented the trunk, primary branch and support of apple trees

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12

Shitu, Saifullahi Sadi, Syed Abd Rahman Syed Abu Bakar, Nura Musa Tahir, Usman Isyaku Bature, and Haliru Liman. "Efficient Thinning Algorithm for Malaysian Car Plate Character Recognition." ELEKTRIKA- Journal of Electrical Engineering 20, no. 3 (2021): 15–25. http://dx.doi.org/10.11113/elektrika.v20n3.286.

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The thinning algorithm is one of the approaches of identifying each character printed on the car plate. Malaysian car plate characters appear in different character sizes, styles, customized printed characters etc. These variations contribute to difficulty in thinning successfully segmented and extracted license plate characters for recognition. To address these problems, an improved thinning operation for Malaysian car plate character recognition is proposed. In this algorithm, samples from segmented and extracted license plates are used for a thinning operation which is passed to Zhang-Suen

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13

Niu, Weilong, Zan Chen, Yihui Zhu, Xiaoguang Sun, and Xuan Li. "Track Line Recognition Based on Morphological Thinning Algorithm." Applied Sciences 12, no. 22 (2022): 11320. http://dx.doi.org/10.3390/app122211320.

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In the field of intelligent driving of freight trains, determining the track line ahead of the train is an important function in the autopilot technology of such trains. Combining the characteristics of freight railway tracks, we conduct an in-depth analysis of the shortcomings of object detection technology in extracting track lines and propose an improved Zhang–Suen (ZS) thinning theory for a railway track line recognition algorithm. Through image preprocessing and single pixel thinning steps, a continuous track line is obtained and then processed by a denoising algorithm to obtain a complet

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14

Ji, Qianru, Haoting Liu, Zhen Tian, Song Wang, Qing Li, and Dewei Yi. "Near-Infrared Forearm Vascular Width Calculation Using Radius Estimation of Tangent Circle." Bioengineering 11, no. 8 (2024): 801. http://dx.doi.org/10.3390/bioengineering11080801.

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In response to the analysis of the functional status of forearm blood vessels, this paper fully considers the orientation of the vascular skeleton and the geometric characteristics of blood vessels and proposes a blood vessel width calculation algorithm based on the radius estimation of the tangent circle (RETC) in forearm near-infrared images. First, the initial infrared image obtained by the infrared camera is preprocessed by image cropping, contrast stretching, denoising, enhancement, and initial segmentation. Second, the Zhang–Suen refinement algorithm is used to extract the vascular skele

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15

Ma, J., V. Yu Tsviatkou, and V. K. Kanapelka. "Image skeletonization based on combination of one- and two-sub-iterations models." Informatics 17, no. 2 (2020): 25–35. http://dx.doi.org/10.37661/1816-0301-2020-17-2-25-35.

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This paper is focused on the field of the skeletonization of the binary image. Skeletonization makes it possible to represent a binary image in the form of many thin lines, the relative position, sizes and shape of which adequately describe the size, shape and orientation in space of the corresponding image areas. Skeletonization has many variety methods. Iterative parallel algorithms provide high quality skeletons. They can be implemented using one or more sub-iterations. In each iteration, redundant pixels, the neighborhoods of which meet certain conditions, are removed layer by layer along

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16

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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17

Wen, Wen, and Wenhui Zhang. "Research on Urban Road Network Extraction Based on Web Map API Hierarchical Rasterization and Improved Thinning Algorithm." Sustainability 14, no. 21 (2022): 14363. http://dx.doi.org/10.3390/su142114363.

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Most existing research on the vector road network is based on GPS trajectory travel information extraction, and urban GPS trajectory data are large and difficult to obtain. Based on this, this study proposes a road network extraction method based on network map API and designs a vector road network based on an improved image-processing algorithm using trajectory data. Firstly, a large number of trajectory data are processed by hierarchical rasterization. The trajectory points of the regional OD matrix are obtained by using the map API interface to generate the trajectory. Then, the image expan

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18

Shen, Jiahui, Lihong Zhang, Laibang Yang, et al. "Testing a Method Based on an Improved UNet and Skeleton Thinning Algorithm to Obtain Branch Phenotypes of Tall and Valuable Trees Using Abies beshanzuensis as the Research Sample." Plants 12, no. 13 (2023): 2444. http://dx.doi.org/10.3390/plants12132444.

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Sudden changes in the morphological characteristics of trees are closely related to plant health, and automated phenotypic measurements can help improve the efficiency of plant health monitoring, and thus aid in the conservation of old and valuable tress. The irregular distribution of branches and the influence of the natural environment make it very difficult to monitor the status of branches in the field. In order to solve the problem of branch phenotype monitoring of tall and valuable plants in the field environment, this paper proposes an improved UNet model to achieve accurate extraction

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19

Chen, Zhangnan, Yaxiong Wang, Siyuan Tong, Chongchong Chen, and Feng Kang. "Grapevine Branch Recognition and Pruning Point Localization Technology Based on Image Processing." Applied Sciences 14, no. 8 (2024): 3327. http://dx.doi.org/10.3390/app14083327.

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The identification of branches and bud points is the key to intelligent pruning of dormant grapevine branches and precise positioning of the pruning point on the branch is an important prerequisite for robotic arm pruning. This study takes Cabernet Sauvignon wine grapes as the experimental object and proposes a depth image-based pruning point localization algorithm based on pruning rules. In order to solve the problem of bud recognition in complex backgrounds, this study adopts a detection method that combines semantic segmentation and target detection. Firstly, the semantic segmentation algor

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20

Li, Xinlei, Jiawei Ma, Shida Yao, Guanxin Chi, and Guangjun Zhang. "A Dual-Modal Robot Welding Trajectory Generation Scheme for Motion Based on Stereo Vision and Deep Learning." Materials 18, no. 11 (2025): 2593. https://doi.org/10.3390/ma18112593.

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To address the challenges of redundant point cloud processing and insufficient robustness under complex working conditions in existing teaching-free methods, this study proposes a dual-modal perception framework termed “2D image autonomous recognition and 3D point cloud precise planning”, which integrates stereo vision and deep learning. First, an improved U-Net deep learning model is developed, where VGG16 serves as the backbone network and a dual-channel attention module (DAM) is incorporated, achieving robust weld segmentation with a mean intersection over union (mIoU) of 0.887 and an F1-Sc

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21

Wu, Jie, and Xiaoqian Zhang. "Tunnel Crack Detection Method and Crack Image Processing Algorithm Based on Improved Retinex and Deep Learning." Sensors 23, no. 22 (2023): 9140. http://dx.doi.org/10.3390/s23229140.

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Tunnel cracks are the main factors that cause damage and collapse of tunnel structures. How to detect tunnel cracks efficiently and avoid safety accidents caused by tunnel cracks effectively is a research hotspot at present. In order to meet the need for efficient detection of tunnel cracks, the tunnel crack detection method based on improved Retinex and deep learning is proposed in this paper. The tunnel crack images collected by optical imaging equipment are used to improve the contrast information of tunnel crack images using the image enhancement algorithm, and this image enhancement algor

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22

Wang, Jun, Xuwei Zhang, Jiaen Liu, Yuanyuan Shi, and Yizhe Huang. "Line-Structured Light Fillet Weld Positioning Method to Overcome Weld Instability Due to High Specular Reflection." Machines 11, no. 1 (2022): 38. http://dx.doi.org/10.3390/machines11010038.

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Fillet welds of highly reflective materials are common in industrial production. It is a great challenge to accurately locate the fillet welds of highly reflective materials. Therefore, this paper proposes a fillet weld identification and location method that can overcome the negative effects of high reflectivity. The proposed method is based on improving the semantic segmentation performance of the DeeplabV3+ network for structural light and reflective noise, and, with MobilnetV2, replaces the main trunk network to improve the detection efficiency of the model. To solve the problem of the irr

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23

Wang, Helong, Dingtao Shen, Wenlong Chen, Yiheng Liu, Yueping Xu, and Debao Tan. "Run-Length-Based River Skeleton Line Extraction from High-Resolution Remote Sensed Image." Remote Sensing 14, no. 22 (2022): 5852. http://dx.doi.org/10.3390/rs14225852.

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Automatic extraction of the skeleton lines of river systems from high-resolution remote-sensing images has great significance for surveying and managing water resources. A large number of existing methods for the automatic extraction of skeleton lines from raster images are primarily used for simple graphs and images (e.g., fingerprint, text, and character recognition). These methods generally are memory intensive and have low computational efficiency. These shortcomings preclude their direct use in the extraction of skeleton lines from large volumes of high-resolution remote-sensing images. I

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24

Honeycutt, Wesley T., and Eli S. Bridge. "UnCanny: Exploiting Reversed Edge Detection as a Basis for Object Tracking in Video." Journal of Imaging 7, no. 5 (2021): 77. http://dx.doi.org/10.3390/jimaging7050077.

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Few object detection methods exist which can resolve small objects (<20 pixels) from complex static backgrounds without significant computational expense. A framework capable of meeting these needs which reverses the steps in classic edge detection methods using the Canny filter for edge detection is presented here. Sample images taken from sequential frames of video footage were processed by subtraction, thresholding, Sobel edge detection, Gaussian blurring, and Zhang–Suen edge thinning to identify objects which have moved between the two frames. The results of this method show distinct co

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Lourenço, Miguel, Diogo Estima, Henrique Oliveira, Luís Oliveira, and André Mora. "Automatic Rural Road Centerline Detection and Extraction from Aerial Images for a Forest Fire Decision Support System." Remote Sensing 15, no. 1 (2023): 271. http://dx.doi.org/10.3390/rs15010271.

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To effectively manage the terrestrial firefighting fleet in a forest fire scenario, namely, to optimize its displacement in the field, it is crucial to have a well-structured and accurate mapping of rural roads. The landscape’s complexity, mainly due to severe shadows cast by the wild vegetation and trees, makes it challenging to extract rural roads based on processing aerial or satellite images, leading to heterogeneous results. This article proposes a method to improve the automatic detection of rural roads and the extraction of their centerlines from aerial images. This method has two main

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26

Anastasia, Rita Widiarti. "Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning." June 28, 2011. https://doi.org/10.5281/zenodo.1063020.

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This paper compares Hilditch, Rosenfeld, Zhang- Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms for Javanese character image recognition. Thinning is an effective process when the focus in not on the size of the pattern, but rather on the relative position of the strokes in the pattern. The research analyzes the thinning of 60 Javanese characters. Time-wise, Zhang-Suen algorithm gives the best results with the average process time being 0.00455188 seconds. But if we look at the percentage of pixels that meet one-pixel thickness, Rosenfelt algorithm gives the best results, with a

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27

Nazarkevych, Mariya, Serhii Dmytruk, Volodymyr Hrytsyk, et al. "Evaluation of the effectiveness of different image skeletonization methods in biometric security systems." International Journal of Sensors, Wireless Communications and Control 10 (December 10, 2020). http://dx.doi.org/10.2174/2210327910666201210151809.

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Background: Systems of the Internet of Things are actively implementing biometric systems. For fast and high-quality recognition in sensory biometric control and management systems, skeletonization methods are used at the stage of fingerprint recognition. The analysis of the known skeletonization methods of Zhang-Suen, Hilditch, Ateb-Gabor with the wave skeletonization method has been carried out and it shows a good time and qualitative recognition results. Methods: The methods of Zhang-Suen, Hildich and thinning algorithm based on Ateb-Gabor filtration, which form the skeletons of biometric f

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28

Li, Bixiong, Yunjun Liu, and Guixing Kuang. "Crack Identification and Quantification of Bridge Concrete Based on YOLOX and Image Processing Techniques." Periodica Polytechnica Civil Engineering, December 5, 2024. https://doi.org/10.3311/ppci.37929.

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The investigation and analysis of bridge distress are critical for the assessment and maintenance of bridge safety, necessitating precise information regarding the condition of the bridge surface. In this study, a deep learning framework for automatically identifying bridge concrete cracks is proposed based on comparing the detection performance of YOLOX, SSD, and Faster R-CNN. The deep learning model YOLOX_s is initially trained and employed to identify bridge concrete cracks, and the detection results demonstrate that the bridge concrete crack identification accuracy rate of the YOLOX_s is 9

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