![]() IEEE Trans Image Process 13(6):782–791Ĭhakraborty S, Singh SK, Chakraborty P (2017) Local quadruple pattern: a novel descriptor for facial image recognition and retrieval. Journal of Mathematical Imaging and Vision 40(3):259–268Ĭampisi P, Neri A, Panci C, Scarano G (2004) Robust rotation-invariant texture classification using a model based approach. IEEE Proceedings Vision, Image, and Signal Processing 145(3):167–172īianconi F, Fernández A (2011) On the occurrence probability of local binary patterns: a theoretical study. IEEE Trans Geosci Remote Sens 33(5):1170–1181Īrof H, Deravi F (1998) Circular neighborhood and 1-DDFT features for texture classification and segmentation. IEEE Trans on Pattern Analysis and Machine Intelligence 28(12):2037–2041Īnys H, He DC (1995) Evaluation of textural and multi polarization radar features for crop classification. Comparison results on the same datasets imply the superiority of the proposed schemes to the conventional methods.Īhonen T, Hadid A, Pietikäinen M (2006) Face recognition with local binary patterns: application to face recognition. Applying the introduced methods to the known benchmarks like Outex (TC3, TC10, TC13, TC12(t) and TC12(h)), UIUC, CUReT and Defect Fabric datasets indicates that even by adopting lower number of features, the classification rate is enhanced from 1% to 9% while the features number are decreased around 10% to 99%. Furthermore, a constraint feature selection method is proposed that selects discriminative features. All of the proposed mapping methods are rotation and illumination invariant. To reduce the size of features, in this paper, some mapping methods are proposed for feature reduction and mapping of these features into a histogram. Merging these histograms increases the features number significantly. Although completed local binary pattern is seemingly the most precise variant of this type of descriptor and provides high classification accuracy by joining three histograms of features. ![]() doi:10.1111/ binary pattern is one of the most known descriptors, which is used for texture classification. Prosthetic failures in dental implant therapy. Sailer I, Karasan D, Todorovic A, Ligoutsikou M, Pjetursson BE. Adhesive sealing of dentin surfaces in vitro: A review. ![]() Nawareg MM, Zidan AZ, Zhou J, Chiba A, Tagami J, Pashley DH. Digital modeling technology for full dental crown tooth preparation. Evaluating ceramic crown margins with digital radiography. Wahle WM, Masri R, Driscoll C, Romberg E. The effect of common dental fixtures on treatment planning and delivery for head and neck intensity modulated proton therapy. ![]() Hu YH, Seum WCTH, Hunzeker A, Muller O, Foote RL, Mundy DW. Cost-utility analysis of an implant treatment in dentistry. Applications of three-dimensional printers in prosthetic dentistry. Kihara H, Sugawara S, Yokota J, Takafuji K, Fukazawa S, Tamada A, et al. Dentist material selection for single-unit crowns: Findings from the National Dental Practice-Based Research Network. Makhija SK, Lawson NC, Gilbert GH, Litaker MS, McClelland JA, Louis DR, et al. ![]()
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