Local binary patterns (LBP) is a type of visual descriptor used for classification in computer vision. LBP is the particular case of the Texture Spectrum model proposed in 1990.[1][2] LBP was first described in 1994.[3][4] It has since been found to be a powerful feature for texture classification; it has further been determined that when LBP is combined with the Histogram of oriented gradients (HOG) descriptor, it improves the detection performance considerably on some datasets.[5] A comparison of several improvements of the original LBP in the field of background subtraction was made in 2015 by Silva et al.[6] A full survey of the different versions of LBP can be found in Bouwmans et al.[7]
^DC. He and L. Wang (1990), "Texture Unit, Texture Spectrum, And Texture Analysis", Geoscience and Remote Sensing, IEEE Transactions on, vol. 28, pp. 509 - 512.
^L. Wang and DC. He (1990), "Texture Classification Using Texture Spectrum", Pattern Recognition, Vol. 23, No. 8, pp. 905 - 910.
^T. Ojala, M. Pietikäinen, and D. Harwood (1994), "Performance evaluation of texture measures with classification based on Kullback discrimination of distributions", Proceedings of the 12th IAPR International Conference on Pattern Recognition (ICPR 1994), vol. 1, pp. 582 - 585.
^T. Ojala, M. Pietikäinen, and D. Harwood (1996), "A Comparative Study of Texture Measures with Classification Based on Feature Distributions", Pattern Recognition, vol. 29, pp. 51-59.
^"An HOG-LBP Human Detector with Partial Occlusion Handling", Xiaoyu Wang, Tony X. Han, Shuicheng Yan, ICCV 2009
^C. Silva, T. Bouwmans, C. Frelicot, "An eXtended Center-Symmetric Local Binary Pattern for Background Modeling and Subtraction in Videos", VISAPP 2015, Berlin, Germany, March 2015.
^T. Bouwmans, C. Silva, C. Marghes, M. Zitouni, H. Bhaskar, C. Frelicot,, "On the Role and the Importance of Features for Background Modeling and Foreground Detection”, arXiv:1611.09099
and 23 Related for: Local binary patterns information
Localbinarypatterns (LBP) is a type of visual descriptor used for classification in computer vision. LBP is the particular case of the Texture Spectrum...
Local ternary patterns (LTP) are an extension of localbinarypatterns (LBP). Unlike LBP, it does not threshold the pixels into 0 and 1, rather it uses...
pound, the currency of Lebanon LittleBigPlanet, a video game series Localbinarypatterns, a type of visual descriptor Long Banga Airport, Malaysia (by IATA...
and rotation invariant texture classification with localbinarypatterns". IEEE Transactions on Pattern Analysis and Machine Intelligence. 24 (7): 971–987...
MLBP may refer to: The record label owned by Mitch Laddie Modified localbinarypatterns This disambiguation page lists articles associated with the title...
cited articles include: "Facial expression recognition based on localbinarypatterns: A comprehensive study" "A real-time automated system for the recognition...
Conference on Computer Vision and Pattern Recognition. "Facial expression recognition based on localbinarypatterns: A comprehensive study". Image & Computing...
The reflected binary code (RBC), also known as reflected binary (RB) or Gray code after Frank Gray, is an ordering of the binary numeral system such that...
In geometry, the binary tiling (sometimes called the Böröczky tiling) is a tiling of the hyperbolic plane, resembling a quadtree over the Poincaré half-plane...
Design Patterns (CommDP) - COMMDP". Archived from the original on 18 March 2017. Retrieved 17 March 2017. Lascano, J. E.; Clyde, S. (2016). A Pattern Language...
rate. An exponential backoff algorithm where b = 2 is referred to as a binary exponential backoff algorithm. When the rate has been reduced in response...
Because two is the base of the binary numeral system, powers of two are common in computer science. Written in binary, a power of two always has the form...
spurious patterns (different from the training patterns). The energy in these spurious patterns is also a local minimum. For each stored pattern x, the...
In computer programming, Base64 is a group of binary-to-text encoding schemes that transforms binary data into a sequence of printable characters, limited...
McCulloch–Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input...
or more classes (classifying instances into one of two classes is called binary classification). While many classification algorithms (notably multinomial...
learn patterns exclusively from unlabeled data. Within such an approach, a machine learning model tries to find any similarities, differences, patterns, and...
Sciences, 1013: 92–109, 2004. O. Lahdenoja, M. Laiho and A. Paasio, "LocalBinaryPattern Feature Vector Extraction with CNN", Int’l Workshop on Cellular Neural...
formed stars are in binary systems. In the model that best explained the data, all stars initially formed as binaries, though some binaries later split up...
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is...
They are, in order, automata in which patterns generally stabilize into homogeneity, automata in which patterns evolve into mostly stable or oscillating...
Global Information