-
1Academic Journal
المؤلفون: Maryani, Any, Anwar, M.Choiroel, Abimanyu, Bagus
المصدر: International Journal of Social Health; Vol. 2 No. 10 (2023): International Journal of Social Health; 725-733 ; 2984-7079 ; 10.58860/ijsh.v2i10
مصطلحات موضوعية: Prostate Volume, Transabdominal Ultrasound, Gradient Vector Flow (GVF), Ultrasound Image
وصف الملف: application/pdf; text/html
-
2Academic Journal
المؤلفون: Atefeh Foroozandeh, Asghar Kerayechiyan, Morteza Gachpazan, Mahdi Momennezhad, Shahrokh Nasseri
المصدر: Iranian Journal of Medical Physics, Vol 9, Iss 3, Pp 169-176 (2012)
مصطلحات موضوعية: 3D Reconstruction, Cubic Bezier Spline Curve, Gradient Vector Flow (GVF) Field, Left Ventricle, Single Photon Emission Tomography (SPECT) Data, Medical physics. Medical radiology. Nuclear medicine, R895-920
وصف الملف: electronic resource
-
3Academic Journal
المؤلفون: Christo Ananth, Karthika.S, Shivangi Singh, Jennifer Christa.J, Gracelyn Ida.I
مصطلحات موضوعية: Automatic segmentation, graph-cuts, gradient vector flow (GVF) active contours, hepatic tumors and liver
Relation: https://doi.org/10.5281/zenodo.844593; https://doi.org/10.5281/zenodo.844594; oai:zenodo.org:844594
-
4
المؤلفون: Wang, Weixing, Su, P. -Y
المصدر: Guangxue Jingmi Gongcheng/Optics and Precision Engineering. 20(12):2781-2790
مصطلحات موضوعية: Blood cell image, Gradient Vector Flow(GVF) Snake, Image classification, Image extraction, Leukocyte classification, Support Vector Machine(SVM)
وصف الملف: print
-
5
المؤلفون: K.S. Hareesh, K. Prabhakar Nayak, Sampath Kumar
المصدر: Procedia Technology. 6:39-48
مصطلحات موضوعية: Landmark, Vector flow, business.industry, Computer science, Structuring element, Radiography, 3D reconstruction, Mathematical morphology, Pedicle segmentation, Gradient Vector Flow (GVF) snakes, Local contrast enhancement, General Earth and Planetary Sciences, Preprocessor, Segmentation, Computer vision, Artificial intelligence, business, Multiscale morphology, General Environmental Science
-
6Conference
المؤلفون: A Khadidos, V Sanchez, Chang-Tsun Li
مصطلحات موضوعية: Active contours, Gradient vector flow (GVF), Balloon forces, Medical image segmentation
Relation: http://hdl.handle.net/10536/DRO/DU:30122355; https://figshare.com/articles/conference_contribution/Active_contours_based_on_weighted_gradient_vector_flow_and_balloon_forces_for_medical_image_segmentation/20767321
-
7
-
8Academic Journal
المؤلفون: Shivakumara, P., Phan, T.Q., Lu, S., Tan, C.L.
المساهمون: COMPUTER SCIENCE
المصدر: Scopus
مصطلحات موضوعية: Arbitrarily oriented text detection, candidate text components (CTC), dominant text pixel, gradient vector flow (GVF), text candidates (TC), text components
Relation: Shivakumara, P., Phan, T.Q., Lu, S., Tan, C.L. (2013). Gradient vector flow and grouping-based method for arbitrarily oriented scene text detection in video images. IEEE Transactions on Circuits and Systems for Video Technology 23 (10) : 1729-1739. ScholarBank@NUS Repository. https://doi.org/10.1109/TCSVT.2013.2255396; http://scholarbank.nus.edu.sg/handle/10635/77864; 000325662200009
-
9Academic Journal
المساهمون: 資訊工程學系, Department of Computer Science
مصطلحات موضوعية: Confocal microscopy, Green fluorescent protein (GFP), Neuron tracing, Gradient vector flow (GVF) snake, Tree structure
Relation: http://hdl.handle.net/11536/7840; JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING; WOS:000266547700001
الاتاحة: http://hdl.handle.net/11536/7840
-
10Academic Journal
-
11
المؤلفون: Hernández Esteban, Carlos
المساهمون: Laboratoire Traitement et Communication de l'Information (LTCI), Télécom ParisTech-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Télécom ParisTech, Francis Schmitt, Télécom ParisTech, Ecole
المصدر: domain_other. Télécom ParisTech, 2004. Français
مصطلحات موضوعية: Placage de textures, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Texture mapping, Visual hull, Deformable model, Enveloppe visuelle, Multi-stéréo, Coherence de silhouettes, [OTHER]domain_other, 3D modeling, Camera calibration, Stereo and silhouette fusion, diffusion multi-résolution du vecteur gradient (GVF), Modèle déformable, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Silhouette coherence, [OTHER] domain_other, octree-based gradient vector flow (GVF), reconstruction 3D, Fusion silhouette, Calibrage, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
وصف الملف: application/pdf
-
12Dissertation/ Thesis
المؤلفون: 王友俊, Wang, Yu-Chun
المساهمون: 周瑞仁, 臺灣大學:生物產業機電工程學研究所
مصطلحات موضوعية: 主動輪廓模式, 邊緣偵測, 橢圓偵測, 梯度向量場, 影像處理, 影像分割, 機器視覺, Active contour model (ACM), Edge detection, Ellipse detection, Gradient vector flow (GVF), Image processing, Mean shift, Segmentation
Relation: Ballard, D. H., and C. M. Brown. 1982. Computer Vision. Prentice Hall, New Jersey. Bennett, N., R. Burridge, and N. Saito. 1999. A method to detect and characterize ellipses using the hough transform. IEEE Trans. on Pattern Analysis and Machine Intelligence 21(7): 652-657. Borgefors, G. 1984. Distance transform in arbitrary dimension. Comp. Vis. Graph. Imag. Proc. 27: 321-345. Burt, P. J., T. H. Hong, and A. Rosenfeld. 1981. Segmentation and estimation of image region properties through cooperative hierarchical computation. IEEE Trans. on Systems, Man, and Cybernetics 11:802-809. Canny, J. 1986. A Computational Approach to Edge Detection. IEEE Trans. on Pattern Analysis and Machine Intelligence 8: 679-698. Chen, C. M., H. S. Lu, and Y. C. Lin. 2000. An early vision-based snake model for ultrasound image segmentation. Ultrasound in Medicine and Biology 26(2): 273-285. Chen, Y. C., and S. C. Lee. 1995. A new method for quadratic curve detection using K-RANSAC with acceleration techniques. Pattern Recognition 28(8): 663-682. Cheng, Y. 1995. Mean shift, mode seeking, and clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence 17(8): 790-798. Chien, C. F., and T. T. Lin. 2002. Leaf area measurement of selected vegetable seedlings using elliptical Hough transform. Transactions of the ASAE 45(5): 1669-1677. Christoudias, C. M., B. Georgescu, and P. Meer. 2002. Synergism in low level vision. 16th International Conference on Pattern Recognition 4:150-155. Quebec City, Canada. Cohen, L. D., and I. Cohen. 1993. Finit-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Trans. on Pattern Analysis and Machine Intelligence 15(11): 1131-1147. Comaniciu, D., V. Ramesh, and P. Meer. 2000. Real-time tracking of non-rigid objects using mean shift. IEEE Conference on Computer Vision and Pattern Recognition 2:142-149. Hilton Head, SC. Comaniciu, D., and P. Meer. 2002. Mean shift, a robust approach toward feature space analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence 24: 603-619. Comaniciu, D. 2003. An algorithm for data-driven bandwidth selection. IEEE Trans. on Pattern Analysis and Machine Intelligence 25(2): 281-288. Danielsson, P. E. 1980. Euclidean distance mapping. Comp. Graph. Imag. Proc. 14: 227-248. Fitzgibbon, A. W., M. Pilu, and R. B. Fischer. 1999. Direct least square fitting of ellipses. IEEE Trans. on Pattern Analysis and Machine Intelligence 21(5): 476-480. Fu, K. S., and J. K. Mui. 1981. A Survey on Image Segmentation. Pattern Recognition 13: 3-16. Fukunaga, K., and L. D. Hostetler. 1975. The Estimation of the Gradient of a Density Function, with Applications in Pattern Recognition. IEEE Trans. on Information Theory IT-21: 32-40. Gath, I., and D. Hoory. 1995. Fuzzy clustering of elliptic ring-shaped clusters. Pattern Recognition Letter 16: 727-741 Gonzalez, R. C., and P. Wintz. 1987. Digital Image Processing (2nd. Ed). Addison-Wesley Harlick, R. M. 1978. Zero-Crossing of Second Directional Derivative Edge Operator. IEEE Trans. on Pattern Analysis and Machine Intelligence 6:58-68. Hjelmas, E., and B. K. Low. 2001. Face Detection: A Survey. Computer Vision and Image Understanding 83: 236–274. Horn, B. K. P., and B. G. Schunck. 1981. Determining optical flow. Artificial intelligence 17: 185-203. Hough, P. V. C. 1962. Method and means for recognizing complex patterns. U.S. Pattern 3069654. Hueckel, M. F. 1971. An Operator Which Locates Edges in Digitised Pictures. Journal of the ACM 18: 113-125. Karaman, M., A. Kutay, and H. Bozdagi. 1995. An adaptive speckle suppression filter for medical ultrasonic imaging. IEEE Trans. on Medical Imaging 14(2):283-292. Kass, M., A. Witkin, and D. Terzoulos. 1988. Snake: Active contour models. International J. Computer Vision 1(4): 321-331. Kittler, J., and J. Illingworth. 1985. On threshold selection using clustering criteria. IEEE Trans. on Systems, Man, and Cybernetics 15:652-655. Kohler, R. A. 1981. A segmentation based on thresholding. Computer Vision, Graphics and Image Processing 15:319-338. Krishnapuram, R., H. Frigui, and O. Nasraoui. 1995. Fuzzy and possibilistic shell clustering algorithms and their application to boundary detection and surface approximation-Part I. IEEE Trans. on Fuzzy Systems 3(1): 29-43 Lefebvre, F., G. Berger, and P. Laugier. 1998. Automatic detection of the boundary of the calcaneus from ultrasound parametric images using an active contour model: Clinical assessment. IEEE Trans. on Medical Imaging 17(1): 45-52. Levine, M. D., and A. Nazif. 1984. An optimal set of image segmentation rules. Pattern Recognition Letters 1:417-422. Mallat, S. G. 1989. A Theory for Multiresolution Signal Decomposition: the Wavelet Representation. IEEE Trans. on Pattern Analysis and Machine Intelligence 11:674-693. Meer, P. and B. Georgescu. 2001. Edge detection with embedded confidence. IEEE Trans. on Pattern Analysis and Machine Intelligence 23(12):1351-1365. Pal, N. R. and S. K. Pal. 1993. A review on image segmentation techniques. Pattern recognition 26(9): 1277-1294. Park, J., and J. M. Keller. 2001. Snake on the watershed. IEEE Trans. on Pattern Analysis and Machine Intelligence 23(10): 1201-1205. Pratt, W. K. 1983. Digital Image Processing. Wiley, New York. Ridler, T. W., and S. Calvard. 1978. Picture thresholding using an iterative selection method. IEEE Trans. on Systems, Man, and Cybernetics SMC-8: 630-632. Sahoo, P. K., S. Soltani, A. K. C. Wong, and Y. C. Chen. 1988. A survey of thresholding techniques. Computer Vision, Graphics and Image Processing 41:233-260. Sapiro, G., and D. L. Ringach. 1996. Anisotropic Diffusion on Multivalued Images with Applications to Color Filtering. IEEE Trans. on Image Processing 5(11): 1582–1586. Shashidhar, N. S., D. S. Jayas, T. G. Crowe, and N. R. Bulley. 1997. Processing of digital image of touching kernels by ellipse fitting. Canadian Agric. Eng. 39(2): 139-142. Shatadal, P., D. S. Jayas, and N. R. Bulley. 1995. Digital image analysis for software separation and classification of touching grains: I. Disconnect algorithm. Transactions of the ASAE 38(2): 635-643. Spann, M., and R. G. Wilson. 1985. A Quad-Tree Approach to Image Segmentation Which Combines Statistical and Spatial Information. Pattern Recognition 18(3/4):257-269. Tsai, W. H. 1985. Moment-preserving thresholding: a new approach. Comput. Vision, Graphics. Image Processing 29: 377-393. Taxt, T., P. J. Flynn, and A. K. Jain. 1989. Segmentation of document images. IEEE Trans. on Pattern Analysis and Machine Intelligence 11:1322-1329. Vincent, L., and P. Soille. 1991. Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Trans. on Pattern Analysis and Machine Intelligence 13(6): 583-598. Visen, N. S., N. S. Shashidhar, J. Paliwal, and D. S. Jayas. 2001. Identification and segmentation of occluding groups of grain kernels in a grain sample image. J. Agric. Eng. Res. 79(2): 159-166. Wang, Y. C., and J. J. Chou. 2004. Automatic segmentation of touching rice kernels with active contour model. Transactions of the ASAE 47(5): 1803-1811. Wang, Y. C., and J. J. Chou. 2006. Segmentation of ellipse-like objects in an image with MFA approach. Journal of Agricultural Machinery 15(1): 15-24. (in Chinese) Wilson, R. G., and M. Spann. 1988. Image Segmentation and Uncertainty. Pattern Recognition and Image Processing Series. Research Studies Press Ltd. Xu, C., and J. L. Prince. 1998. Snakes, shapes, and gradient vector flow. IEEE Trans. on Image Processing 7(3): 359-363. Yang, F., and Tianzi Jiang. 2001. Cell image segmentation with kernel-based dynamic clustering and an ellipsoidal cell shape model. Journal of Biomedical Informatics. 34: 67-73 Yuen, H. K., J. Illingworth, and J. Kittler. 1989. Detecting partially occluded ellipses using the Hough transform. Image and Vision Computing 7(1): 31-37. Yuen, P. C., Y. Y. Wong, and C. S. Tong. 1996. Contour detection using enhanced snakes algorithm. Electronics Letters 32(3): 202-204. Yun, H. S., W. O. Lee, H. Chung, H. D. Lee, J. R. Son, K. H. Cho, and W. K. Park. 2002. A Computer Vision System for Rice Kernel Quality Evaluation. 2002 ASAE Annual Meeting. Paper number 023130. Zhu, S. C. and A. Yuille. 1996. Region growing: unifying snakes, region growing, and Bayes/MDL for Multiband image segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence 18(9): 884-900.; en-US; http://ntur.lib.ntu.edu.tw/handle/246246/52896