Abstract
In previous chapter, the weaknesses of conventional segmentation methods have been identified. This concludes the desired segmentation criteria in order to guide the mechanism of the proposed framework of segmentation. The segmentation is performed to partition the hand bone from its background and soft-tissue region in the beginning of this chapter. The challenges of hand bone segmentation are the overlapping intensity between the soft-tissue region and the spongy bone region within the hand bone. Three modules of techniques will be discussed and implemented to solve the problem in this chapter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Nakib A, Oulhadj H, Siarry P (2010) Image thresholding based on Pareto multiobjective optimization. Eng Appl Artif Intell 23:313–320
Chen S-D, Rahman Ramli A (2004) Preserving brightness in histogram equalization based contrast enhancement techniques. Digital Signal Process 14:413–428
Yu W, Qian C, Baeomin Z (1999) Image enhancement based on equal area dualistic sub-image histogram equalization method. IEEE Trans Consum Electron 45:68–75
Cao F, Huang HK, Pietka E, Gilsanz V (2000) Digital hand atlas and web-based bone age assessment: system design and implementation. Comput Med Imaging Graph 24:297–307
Sim KS, Tso CP, Tan YY (2007) Recursive sub-image histogram equalization applied to gray scale images. Pattern Recogn Lett 28:1209–1221
Kim M, Min C (2008) Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement. IEEE Trans Consum Electron 54:1389–1397
Kim T, Paik J (2008) Adaptive contrast enhancement using gain-controllable clipped histogram equalization. IEEE Trans Consum Electron 54:1803–1810
Seungjoon Y, Jae Hwan O, Yungfun P (2003) Contrast enhancement using histogram equalization with bin underflow and bin overflow. In: Proceedings of international conference on image processing, 2003 (ICIP 2003) (ed), vol 1, pp I-881-4
Perona P (1989) Anisotropic diffusion processes in early vision. In: Multidimensional signal processing workshop, 1989. Sixth edition, p 68
Witkin A (1983) Scale-space filtering. In 8th international joint conference of artificial intelligence. (ed), Vol 2, pp 1019–22
Perona P, Malik J (1990) Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 12:629–639
Aja-Fernández S, Vegas-Sánchez-Ferrero G, MartÃn-Fernández M, Alberola-López C (2009) Automatic noise estimation in images using local statistics. Additive and multiplicative cases. Image Vis Comput 27:756–770
Yongjian Y, Acton ST (2002) Speckle reducing anisotropic diffusion. IEEE Trans Image Process 11:1260–1270
Fuller W (2009) Sampling Statistics. Vol. 560, Wiley, London
Capuzzo Dolcetta I, Ferretti R (2001) Optimal stopping time formulation of adaptive image filtering. Appl Math Optim 43:245–258
Papandreou G, Maragos P (2005) A cross-validatory statistical approach to scale selection for image denoising by nonlinear diffusion. In: IEEE computer society conference on computer vision and pattern recognition (CVPR’05) (ed), Vol. 1, IEEE computer society, pp 625–30
Sun J, Xu Z (2010) Scale selection for anisotropic diffusion filter by Markov random field model. Pattern Recogn 43:2630–2645
Gerig G, Kubler O, Kikinis R, Jolesz FA (1992) Nonlinear anisotropic filtering of MRI data. IEEE Trans Med Imaging 11:221–232
Haralick RM, Shanmugam K, Dinstein IH (1973) Textural Features for Image Classification. IEEE Trans Syst, Man Cybern 3:610–621
Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7:1–13
Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 The Author(s)
About this chapter
Cite this chapter
Hum, Y.C. (2013). Design and Implementation. In: Segmentation of Hand Bone for Bone Age Assessment. SpringerBriefs in Applied Sciences and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-4451-66-6_3
Download citation
DOI: https://doi.org/10.1007/978-981-4451-66-6_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-4451-65-9
Online ISBN: 978-981-4451-66-6
eBook Packages: EngineeringEngineering (R0)