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Artykuły w czasopismach na temat „Snake Segmentation”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Handayani, Astri, Andriyan B. Suksmono, Tati L. R. Mengko, and Akira Hirose. "Blood Vessel Segmentation in Complex-Valued Magnetic Resonance Images with Snake Active Contour Model." International Journal of E-Health and Medical Communications 1, no. 1 (2010): 41–52. http://dx.doi.org/10.4018/jehmc.2010010104.

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Accurate blood vessel segmentation plays a crucial role in non-invasive blood flow velocity measurement based on complex-valued magnetic resonance images. We propose a specific snake active contour model-based blood vessel segmentation framework for complex-valued magnetic resonance images. The proposed framework combines both magnitude and phase information from a complex-valued image representation to obtain an optimum segmentation result. Magnitude information of the complex-valued image provides a structural localization of the target object, while phase information identifies the existenc

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Huang, Xing, Haozhi Zhu, and Jiexin Wang. "Adoption of Snake Variable Model-Based Method in Segmentation and Quantitative Calculation of Cardiac Ultrasound Medical Images." Journal of Healthcare Engineering 2021 (July 26, 2021): 1–13. http://dx.doi.org/10.1155/2021/2425482.

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This paper intends to explore the effect of the enhanced snake variable model in the segmentation of cardiac ultrasound images and its adoption in quantitative measurement of cardiac cavity. First, the basic principles of the traditional snake model and the gradient vector flow (GVF) snake model are explained. Then, an ellipsoid model is constructed to obtain the initial contour of the heart based on the three-dimensional volume of cardiac ultrasound image, and a discretized triangular mesh model is generated. Finally, the vortical gradient vector flow (VGVF) external force field is introduced

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Huang, Wen Bo, Yang Yan, and Yun Ji Wang. "Boundary Segmentation Based on Improved GVF Snake Model." Advanced Materials Research 756-759 (September 2013): 3920–23. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3920.

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The gradient vector flow (GVF) Snake models are active contour models: they lock onto nearby edges, localizing them accurately. GVF refers to the definition of a bidirectional external force that can capture the object boundaries from either sides and can deal with concave regions. However, we find that there is a main disadvantage of GVF Snakes---- there are some critical points in the model, the critical points must be included in the initial contour or must not be contained internal, and otherwise, it could not converge to the correct boundary. To solve this problem, we propose an improved

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Wang, Jiyuan, Hanqing Zou, Shaokun Sun, Wenqian Xu, and Jie Jin. "Edge Segmentation Algorithm‐Based Prevention of Recurrent Laryngeal Nerve Injury in Treatment of Thyroid Nodules Using Ultrasound Images." Scientific Programming 2021 (September 14, 2021): 1–7. http://dx.doi.org/10.1155/2021/6583110.

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The study was aimed to explore the segmentation effects of different algorithms on thyroid nodule ultrasound images, so as to better protect the recurrent laryngeal nerve during thyroid surgery. Specifically, 186 patients with thyroid nodules were selected as the research objects. The segmentation performances of the gradient vector flow (GVF) Snake, Watershed, and Snake algorithms were compared from 6 aspects of image segmentation effects, pixel accuracy (PA), Intersection over Union (IOU) value, algorithm running time, postoperative recurrent laryngeal nerve injury, intraoperative bleeding v

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5

Zhang, Xue Fei. "An Improved Directional GVF Snake." Applied Mechanics and Materials 644-650 (September 2014): 4501–4. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.4501.

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Gradient Vector Flow (GVF) Snake has been extensively utilized in handling image segmentation and classification problems. However, GVF Snake has a drawback in that it sometimes may fail to stop the snake at weak edges, especially at the locations where a weak edge is very close to a strong one or some noise. To guide the snake toward the appropriate edges, we have added gradient directional information to the external image force to create a “directional snake”. Experiments prove that the new model limits the influence of false edge, avoid the edge leak, and obtains desired segmentation resul

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6

Wu, Jun Peng, and Hai Tao Guo. "Underwater Sonar Image Segmentation Based on Snake Model." Applied Mechanics and Materials 448-453 (October 2013): 3675–78. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.3675.

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The underwater sonar image segmentation has been a topic of research for decades. Underwater sonar image is based on the interaction by the echo signal of sound toward the underwater objects or targets. Because of the serious noises polution and the dim target edge, the contrast and resolution of sonar images are obtaind in a decreased quanlity. This paper proposes an improved snake model that focuses on solving underwater target detection and recognition. According to the traditional snake model, it is defined as an energy minimizing spline which is influenced by external constraint forces, a

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7

Lan, Hong, and Le Quan Min. "Improved Snake Model Algorithm with Application in Liver Image Segmentation." Applied Mechanics and Materials 263-266 (December 2012): 2643–48. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2643.

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Snake model is one of classical active contour models, and is widely used in the image segmentation. But it has defects of sensitive to the initial contour and lack of curvature constraints. This paper presents an improved Snake model algorithm, which initializes contour by maker control watershed algorithm and adds an external force related with the curve shape into the energy function of Snake model to solve the problem about curvature constraints. Testing on the Magnetic Resonance (MR) images of the abdomen for liver image segmentation proves that the new algorithm can achieve good results.

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8

Midha, Sugandhi. "Performance Evaluation Study of Active Contour Models in Medical Imaging." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 6 (2013): 2703–8. http://dx.doi.org/10.24297/ijct.v11i6.3045.

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Over the past years image segmentation has played an important role in medical imaging. Segmented images are used for a number of applications such as computer aided surgery, treatment planning, diagnosis, study of anatomical structures and many more. Deformable models provide a general method of performing non-rigid object segmentation. They offer an attractive approach to overcome the limitations of traditional low level segmentation approaches. A snake is a flexible deformable model which can be matched to an image contour by energy minimisation. Snakes are a powerful technique in segmentin

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9

Li, Yin Wei, Wen Ming Huang, and Wen Zheng Cai. "CSF Cell Images Segmentation Using a Hybrid Model Based on Watershed and Snake." Applied Mechanics and Materials 321-324 (June 2013): 1051–54. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1051.

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In this paper, a new image segmentation approach is proposed based on the morphological watershed transform and an improved balloon snake algorithm for reducing the incorrect segmenting rate that caused by uneven dyeing of Cerebrospinal Fluid (CSF) cells. Firstly, a marker-controlled watershed pre-segmentation was applied to resolve the over-segmentation problem of the watershed and eliminate the approximate contour of CSF cells. Secondly, due to the weak boundary of some cytoplasm, we performed a coarse segmentation by using an improved balloon snake to dilate the watershed result. Finally, a

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10

GIRALDI, GILSON A., and ANTONIO A. F. OLIVEIRA. "INVARIANT SNAKES AND INITIALIZATION OF DEFORMABLE MODELS." International Journal of Image and Graphics 04, no. 03 (2004): 363–84. http://dx.doi.org/10.1142/s0219467804001464.

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Parametric snake models are deformable models very useful for boundary extraction and tracking. Despite their abilities, the non-invariance of the internal energy under affine transformations and the non-convexity of the model energy are known limitations for most of these methods. The former has been addressed in the context of active shape models. The latter can be addressed through Dual contour approaches as well as an automatic procedure to initialize the model closer to the desired boundary. In this paper we first analyze the effects of reparameterization for invariant snake models throug

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11

Shi, Zhuo, and Fang Li. "Active Subdivision Snake Scheme." Applied Mechanics and Materials 44-47 (December 2010): 3917–21. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3917.

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Active contours or Snakes are extensively used in computer vision and image processing applications, to locate the object boundaries. Low convergence speed and high complexity in computing have significantly limited their utilities. By taking these problems into consideration, the present research focuses on a novel way in rapid image segmentation methodology. This method utilizes subdivision curves in combination with the Gradient Vector Flow (GVF) snakes to overcome these problems. GVF snakes use region energy minimization which is superior to the mass-spring model of the Tamed snake in whol

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12

Jiang, Hui Yan, and Xi He Gao. "Semi-Automatic Liver Segmentation Using Improved GVF Snake Model." Advanced Materials Research 121-122 (June 2010): 435–40. http://dx.doi.org/10.4028/www.scientific.net/amr.121-122.435.

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Snakes are extensively used in computer vision and Image processing. However, when it comes to the liver segmentation from computed tomography (CT) image, the application of the models is limited because it can not extend to certain boundary indentations of the liver. In order to solve this problem, we developed an improved GVF snake model by adding an external force field which can efficiently attract the initial contour to these depression areas, such as the top of the left lobe of liver. The proposed method includes two steps. Firstly, combined with the threshold method and the morphology o

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13

Gao, Shouwei, Yi Cheng, Shujun Mao, Xiangyu Fan, and Xingyang Deng. "SSVEP-Enhanced Threat Detection and Its Impact on Image Segmentation." International Journal on Semantic Web and Information Systems 20, no. 1 (2024): 1–20. http://dx.doi.org/10.4018/ijswis.336550.

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Selective attention, essential in discerning visual stimuli, enables the identification of threats such as snakes—a prime evolutionary influence on the human visual system. This phenomenon is encapsulated in snake detection theory (SDT), which posits that our ancestors' need to recognize these predators led to specialized perceptual abilities. This investigation utilizes steady-state visual evoked potentials (SSVEP) alongside the random image structure evolution technique, which systematically increases visual clarity through the interpolation of random noise, to probe the neural mechanisms un

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14

Al-Tamimi, Mohammed Sabbih Hamoud. "Hybrid Methodology for Image Segmentation Based on Active Contour Module and Alpha-Shape Theory." Modern Applied Science 10, no. 11 (2016): 30. http://dx.doi.org/10.5539/mas.v10n11p30.

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The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image fiel

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15

Cheng, Yuanzhi, Xin Hu, Ji Wang, Yadong Wang, and Shinichi Tamura. "Accurate Vessel Segmentation With Constrained B-Snake." IEEE Transactions on Image Processing 24, no. 8 (2015): 2440–55. http://dx.doi.org/10.1109/tip.2015.2417683.

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Lu, R., and Y. Shen. "Noisy Image Segmentation by Modified Snake Model." Journal of Physics: Conference Series 48 (October 1, 2006): 369–72. http://dx.doi.org/10.1088/1742-6596/48/1/069.

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Yuen, P. C. "Dividing snake algorithm for multiple object segmentation." Optical Engineering 41, no. 12 (2002): 3177. http://dx.doi.org/10.1117/1.1517289.

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18

Saadatmand-Tarzjan, M. "Self-affine snake for medical image segmentation." Pattern Recognition Letters 59 (July 2015): 1–10. http://dx.doi.org/10.1016/j.patrec.2015.03.006.

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Dagher, Issam, and Kamal El Tom. "WaterBalloons: A hybrid watershed Balloon Snake segmentation." Image and Vision Computing 26, no. 7 (2008): 905–12. http://dx.doi.org/10.1016/j.imavis.2007.10.010.

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Sun, Jinyang, Fangjun Luan, and Hanhui Wu. "Optic Disc Segmentation by Balloon Snake with Texture from Color Fundus Image." International Journal of Biomedical Imaging 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/528626.

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A well-established method for diagnosis of glaucoma is the examination of the optic nerve head based on fundus image as glaucomatous patients tend to have larger cup-to-disc ratios. The difficulty of optic segmentation is due to the fuzzy boundaries and peripapillary atrophy (PPA). In this paper a novel method for optic nerve head segmentation is proposed. It uses template matching to find the region of interest (ROI). The method of vessel erasing in the ROI is based on PDE inpainting which will make the boundary smoother. A novel optic disc segmentation approach using image texture is explore

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21

LIU, JEN-CHANG, and WEN-LIANG HWANG. "ACTIVE CONTOUR MODEL USING WAVELET MODULUS FOR OBJECT SEGMENTATION AND TRACKING IN VIDEO SEQUENCES." International Journal of Wavelets, Multiresolution and Information Processing 01, no. 01 (2003): 93–113. http://dx.doi.org/10.1142/s0219691303000062.

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We propose an integrated wavelet-based framework of the active contour model (snake) for segmentation and motion tracking of deformable objects in video sequences. The input image frame is represented by means of wavelet transform. First, the moduli of wavelet transform coefficients are used in a multi-resolution motion estimation process to find the initial snake contour in the current frame. The presented multi-resolution motion estimation methods allow a larger movement of the tracked object than does traditional image-based motion estimation. Secondly, the wavelet transform modulus at each

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22

Zhou, Wu, and Yaoqin Xie. "Interactive Medical Image Segmentation Using Snake and Multiscale Curve Editing." Computational and Mathematical Methods in Medicine 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/325903.

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Image segmentation is typically applied to locate objects and boundaries, and it is an essential process that supports medical diagnosis, surgical planning, and treatments in medical applications. Generally, this process is done by clinicians manually, which may be accurate but tedious and very time consuming. To facilitate the process, numerous interactive segmentation methods have been proposed that allow the user to intervene in the process of segmentation by incorporating prior knowledge, validating results and correcting errors. The accurate segmentation results can potentially be obtaine

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23

Sigit, Riyanto, Moch Rochmad, Tri Harsono, and Farah Devi Isnanda. "Hand Wrist Bone Identification Using Quadrant Ballon Snake." Indonesian Journal of Electrical Engineering and Computer Science 8, no. 2 (2017): 335. http://dx.doi.org/10.11591/ijeecs.v8.i2.pp335-342.

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In this research, hand wrist bone Identification for human forensic is discussed. Hand wrist bone is one of the effective methods used in the forensic science for age identification. There are four techniques used in this research: cropping image, preprocessing, Quadrant Ballon Snake and identification. The first step is to crop an image on metaphysis and epiphysis bone. The second step is preprocessing using morphology and edge detection. The third step is to apply Quadrant Ballon Snake to segment hand wrist bone. The last step is to use ratio metaphysis and epiphysis to identify a person. Th

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24

Wang, Yuanquan. "Research on Boundary Concavities Segmentation via Snake Models." Journal of Computer Research and Development 42, no. 7 (2005): 1179. http://dx.doi.org/10.1360/crad20050713.

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Hu, Min. "Cell Nucleus Segmentation Based on Fuzzy Growing Snake." Journal of Computer Research and Development 43, no. 9 (2006): 1530. http://dx.doi.org/10.1360/crad20060907.

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Liu, Fan, Binsheng Zhao, Peter K. Kijewski, Liang Wang, and Lawrence H. Schwartz. "Liver segmentation for CT images using GVF snake." Medical Physics 32, no. 12 (2005): 3699–706. http://dx.doi.org/10.1118/1.2132573.

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Wang, Yue, and Eam Khwang Teoh. "Dynamic B-snake model for complex objects segmentation." Image and Vision Computing 23, no. 12 (2005): 1029–40. http://dx.doi.org/10.1016/j.imavis.2005.07.006.

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Wang, Qun Long. "Human Motion Tracking Based on B-Spline Snake Algorithm." Advanced Materials Research 706-708 (June 2013): 1886–89. http://dx.doi.org/10.4028/www.scientific.net/amr.706-708.1886.

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A new method for tracking of moving human objects is presented. The developed algorithm is based on B-spline Snake model. The Snake algorithm accesses the object contour through minimizing the energy; the object contour in each frame is presented through three B-spline curve. This approach gets the change image with double thresholds image segmentation between the neighboring frames, it could detect moving human objects with high quality and locate objects approximately. The contour extracts from the last frame put at the approximate position as the B-spline Snake model initialization. It acco

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Bougrine, Asma, Rachid Harba, Raphael Canals, Roger Ledee, Meryem Jabloun, and Alain Villeneuve. "Segmentation of Plantar Foot Thermal Images Using Prior Information." Sensors 22, no. 10 (2022): 3835. http://dx.doi.org/10.3390/s22103835.

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Diabetic foot (DF) complications are associated with temperature variations. The occurrence of DF ulceration could be reduced by using a contactless thermal camera. The aim of our study is to provide a decision support tool for the prevention of DF ulcers. Thus, the segmentation of the plantar foot in thermal images is a challenging step for a non-constraining acquisition protocol. This paper presents a new segmentation method for plantar foot thermal images. This method is designed to include five pieces of prior information regarding the aforementioned images. First, a new energy term is add

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Tang, Jiaxi, Yaqin Zhao, Liqi Feng, and Wenxuan Zhao. "Contour-Based Wild Animal Instance Segmentation Using a Few-Shot Detector." Animals 12, no. 15 (2022): 1980. http://dx.doi.org/10.3390/ani12151980.

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Camera traps are widely used in wildlife research, conservation, and management, and abundant images are acquired every day. Efficient real-time instance segmentation networks can help ecologists label and study wild animals. However, existing deep convolutional neural networks require a large number of annotations and labels, which makes them unsuitable for small datasets. In this paper, we propose a two-stage method for the instance segmentation of wildlife, including object detection and contour approximation. In the object detection stage, we use FSOD (few-shot object detection) to recogni

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Syaputri, Sintha, and Zulkarnain. "SEGMENTASI CITRA THORAX PARU-PARU MANUSIA DARI SINAR-X MENGGUNAKAN METODE KONTUR AKTIF." JOURNAL ONLINE OF PHYSICS 4, no. 2 (2019): 8–10. http://dx.doi.org/10.22437/jop.v4i2.7577.

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Research on medical image objects in the form of lung images of thoracic X-Rayis increasingly being developed because the information contained in medical images is used to analyze and determine the shape of the lungs. The process of normalization and image improvement is needed and continued with the segmentation process using the right method. The active snake contour method is used because it is resistant to the noise around the object. The research has been usedthe Matlab software GUI program version R2015a. The image through the initial preprocessing stage is converted into a grayscale im

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Li, Baoxian, Hao Xu, Xin Jin, et al. "An Optimized Dual-View Snake Unet Model for Tunnel Lining Crack Detection." Buildings 15, no. 5 (2025): 777. https://doi.org/10.3390/buildings15050777.

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The prompt and accurate detection of tunnel lining cracks is essential for maintaining the safety and reliability of tunnels. Deep learning-based approaches have significantly advanced automated crack detection, delivering improved efficiency and precision in tunnel inspection. Nevertheless, the intricate characteristics of cracks, manifesting as fine, elongated, and irregular structures, pose substantial challenges for deep learning-based semantic segmentation networks, hindering their ability to achieve comprehensive and accurate identification. Aiming to tackle these challenges, this paper

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Rajalakshmi, T., U. Snekhalatha, and Jisha Baby. "SEGMENTATION OF LIVER TUMOR USING FAST GREEDY SNAKE ALGORITHM." Biomedical Engineering: Applications, Basis and Communications 31, no. 02 (2019): 1950013. http://dx.doi.org/10.4015/s1016237219500133.

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Back Ground: Liver tumors are a type of growth found in the liver which can be categorized as malignant or benign. It is also called as hepatic tumors. Early stage detection of tumor could be treated at a faster phase; if it is left undiagnosed it may lead to several complications. Traditional method adopted for diagnosis can be time consuming, error-prone and also requires an experts study. Hence a non invasive diagnostic method is required which overcomes the flaws of conventional method. Liver segmentation from CT images in post processing techniques not only is an essential prerequisite, b

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Yezzi, A., S. Kichenassamy, A. Kumar, P. Olver, and A. Tannenbaum. "A geometric snake model for segmentation of medical imagery." IEEE Transactions on Medical Imaging 16, no. 2 (1997): 199–209. http://dx.doi.org/10.1109/42.563665.

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Ruan, Yudi, Di Wang, Yijing Yuan, Shixin Jiang, and Xianyi Yang. "SKPNet: snake KAN perceive bridge cracks through semantic segmentation." Intelligence & Robotics 5, no. 1 (2025): 105–18. https://doi.org/10.20517/ir.2025.07.

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As the demands for ensuring bridge safety continue to rise, crack detection technology has become more crucial than ever. In this context, deep learning methods have been widely applied in the field of intelligent crack detection for bridges. However, existing methods are often constrained by complex backgrounds and computational limitations, struggling with issues such as weak crack continuity and insufficient detail representation. Inspired by biological mechanisms, a dynamic snake convolution (DSC) with tubular offsets is incorporated to tackle these challenges effectively. Additionally, a

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Pardo, J. M., D. Cabello, and J. Heras. "A snake for model-based segmentation of biomedical images." Pattern Recognition Letters 18, no. 14 (1997): 1529–38. http://dx.doi.org/10.1016/s0167-8655(97)00135-9.

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Kronfeld, Thomas, David Brunner, and Guido Brunnett. "Snake-Based Segmentation of Teeth from Virtual Dental Casts." Computer-Aided Design and Applications 7, no. 2 (2010): 221–33. http://dx.doi.org/10.3722/cadaps.2010.221-233.

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Jinn Ho and Wen-Liang Hwang. "Automatic Microarray Spot Segmentation Using a Snake-Fisher Model." IEEE Transactions on Medical Imaging 27, no. 6 (2008): 847–57. http://dx.doi.org/10.1109/tmi.2008.915697.

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Chaudhry, Asmatullah, Mehdi Hassan, Asifullah Khan, Seung Ho Choi, and Jin Young Kim. "Automatic Carotid Artery Image Segmentation using Snake Based Model." Journal of Korea Navigation Institute 17, no. 1 (2013): 115–22. http://dx.doi.org/10.12673/jkoni.2013.17.01.115.

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Chen, Qiang, Fang Quan, Jiajing Xu, and Daniel L. Rubin. "Snake model-based lymphoma segmentation for sequential CT images." Computer Methods and Programs in Biomedicine 111, no. 2 (2013): 366–75. http://dx.doi.org/10.1016/j.cmpb.2013.05.019.

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Hu, Xiaojuan, Zhaobang Liu, Xiaodong Yang, et al. "An Unsupervised Tongue Segmentation Algorithm Based on Improved gPb-owt-ucm." Journal of Medical Imaging and Health Informatics 11, no. 3 (2021): 688–96. http://dx.doi.org/10.1166/jmihi.2021.3317.

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Background and Objective: The modernization of tongue diagnosis is an important research in Traditional Chinese Medicine. Accurate and practical tongue segmentation method is a premise in subsequent analyses. In this paper, an unsupervised tongue segmentation method is proposed based on an improved gPb-owt-ucm algorithm. The gPb-owt-ucm is short for global pixel point, oriented watershed transform and ultrametric contour map. Methods: Improved gPb-owt-ucm algorithm is adopted in this paper because of its powerful contour detection capabilities. The boundary feasibility of each pixel is calcula

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P Sajan, Priya, and S. S. Kumar. "GVF snake algorithm-a parallel approach." International Journal of Engineering & Technology 7, no. 1.1 (2017): 101. http://dx.doi.org/10.14419/ijet.v7i1.1.9206.

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Multicore architecture is an emerging computer technology where multiple processing element will be acting as independent processing cores by sharing a common memory. Digital image segmentation is a widely used medical imaging application to extract regions of interest. GVF Active Contour is a region based segmentation technique which extracts curved and irregular shaped regions by diffusing gradient vectors and by the influence of internal and external forces. This requires prior knowledge on the geometric position and anatomical structures to locate the specific region defined within an imag

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Jawaid, Muhammad Moazzam, Bushra Naz Soomro, Sajjad Ali Memon, and Noor-ur-Zaman Leghari. "Effective Image Segmentation using Composite Energy Metric in Levelset Based Curve Evolution." January 2019 38, no. 1 (2019): 175–84. http://dx.doi.org/10.22581/muet1982.1901.14.

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Accurate segmentation of anatomical organs in medical images is a complex task due to wide inter-patient variability and several acquisition dependent artefacts. Moreover, image noise, low contrast and intensity inhomogeneity in medical data further amplifies the challenge. In this work, we propose an effective yet simple algorithm based on composite energy metric for precise detection of object boundaries. A number of methods have been proposed in literature for image segmentation; however, these methods employ individual characteristics of image including gradient, regional intensity or text

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Zhou, Zhi Heng, and Hui Qiang Zhong. "Image Segmentation Based on Poisson Equation." Applied Mechanics and Materials 284-287 (January 2013): 3131–34. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3131.

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Image segmentation is an important part of the image processing. Currently, image segmentation methods are mainly the threshold-based segmentation method, the region-based segmentation method, the edge-based segmentation method and the Snake model based on energy function etc. This paper presents a novel image segmentation method based on the Poisson equation. The goal of the segmentation method is to divide the image into two homogeneous parts, the boundary portion and the non-boundary portion, which have similar gray values in homogeneous part. The key of the method is to build a Poisson equ

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Wang Yan, 王燕, 李积英 Li Jiying, 杨宜林 Yang Yilin, 俞永乾 Yu Yongqian, and 王景慧 Wang Jinghui. "Breast Tumor Segmentation Based on SLIC and GVF Snake Algorithm." Laser & Optoelectronics Progress 57, no. 14 (2020): 141023. http://dx.doi.org/10.3788/lop57.141023.

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Wang, Qi, and Gui Rong Weng. "Application of Snakes Model in Metal Fracture Images Processing." Advanced Materials Research 659 (January 2013): 139–42. http://dx.doi.org/10.4028/www.scientific.net/amr.659.139.

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This paper is using contour line model (Snake model) and the principle of mathematical morphology to process the SEM, AFM, TEM image of metal failure.Including the image denoising and enhancement, target segmentation. Because of SEM, AFM, TEM image can better reaction the metal fracture failure in microstructure, suitable to analyze its image characteristics, then combined with the method of the paper uses to process the scanning image. The experimental results show that, using the Snake model for metal failure image processing is practical and effective feasible, can obviously improve image q

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Khunteta, Ajay, and D. Ghosh. "Object Boundary Detection Using Active Contour Model via Multiswarm PSO with Fuzzy-Rule Based Adaptation of Inertia Factor." Advances in Fuzzy Systems 2016 (2016): 1–20. http://dx.doi.org/10.1155/2016/6179576.

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Active contour models, colloquially known as snakes, are quite popular for several applications such as object boundary detection, image segmentation, object tracking, and classification via energy minimization. While energy minimization may be accomplished using traditional optimization methods, approaches based on nature-inspired evolutionary algorithms have been developed in recent years. One such evolutionary algorithm that has been used extensively in active contours is the particle swarm optimization (PSO). However, conventional PSO converges slowly and gets trapped in local minimum easi

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Snekhalatha, U., T. Rajalakshmi, M. Gopikrishnan, and Nilkantha Gupta. "Computer-based automated analysis of X-ray and thermal imaging of knee region in evaluation of rheumatoid arthritis." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 231, no. 12 (2017): 1178–87. http://dx.doi.org/10.1177/0954411917737329.

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The aim and objectives of the study are as follows: (1) to perform automated segmentation of knee X-ray images using fast greedy snake algorithm and feature extraction using gray level co-occurrence matrix method, (2) to implement automated segmentation of knee thermal image using RGB segmentation method and (3) to compare the features extracted from the segmented knee region of X-ray and thermal images in rheumatoid arthritis patients using a biochemical method as standard. In all, 30 rheumatoid arthritis patients and 30 age- and sex-matched healthy volunteers were included in the study. X-ra

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Darvish, Arman, and Shahryar Rahnamayan. "Optimal Parameter Setting of Active-Contours Using Differential Evolution and Expert-Segmented Sample Image." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 6 (2012): 677–86. http://dx.doi.org/10.20965/jaciii.2012.p0677.

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Generally, tissue extraction (segmentation) is one of the most challenging tasks in medical image processing. Inaccurate segmentation propagates errors to the subsequent steps in the image processing chain. Thus, in any image processing chain, the role of segmentation is in fact critical because it has a significant impact on the accuracy of the final results, such as those of feature extraction. The appearance of variant noise types makes medical image segmentation a more complicated task. Thus far, many approaches for image segmentation have been proposed, including the well-known active con

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Feng, Yafeng, and Xianguo Liu. "Application of Video Processing Technology Based on Diffusion Equation Model in Basketball Analysis." Advances in Mathematical Physics 2021 (December 26, 2021): 1–12. http://dx.doi.org/10.1155/2021/7522973.

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Video event detection and annotation work is an important content of video analysis and the basis of video content retrieval. Basketball is one of the most popular types of sports. Event detection and labeling of basketball videos can help viewers quickly locate events of interest and meet retrieval needs. This paper studies the application of anisotropic diffusion in video image smoothing, denoising, and enhancement. An improved form of anisotropic diffusion that can be used for video image enhancement is analyzed. This paper studies the anisotropic diffusion method for coherent speckle noise

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