Modified Local Binary Pattern Algorithm for Feature Dimensionality Reduction

Title:Modified Local Binary Pattern Algorithm for Feature Dimensionality Reduction

Volume: 14 Issue: 3

Author(s): Manish Kumar*, Rahul Gupta, Kota S. Raju and Dinesh Kumar

Affiliation:

• Department of Electronic Science, Kurukshetra University, Haryana,India

Keywords: Face recognition, Local Binary Pattern (LBP), modified recognition algorithm, fast response, Chi-Square Transformation (CST), Asymmetric Principal Component Analysis (APCA).

Abstract:

Background: Bio metric authentication is becoming popular now a days and becoming integral part of IoT and other systems. Face recognition is one of the major and important aspect of bio metric systems after the fingerprint.

Objective: A face recognition algorithm with feature dimensionality reduction is proposed which is very much required in recognition system for high speed and accuracy.

Methods: The proposed algorithm is based on a variant of Local Binary Pattern (LBP) for face detection and recognition. The features of each block of face image is extracted and then global feature of face is constructed from super histogram.

Results: For recognition, traditional methods are used. The query image is compared with the data set (ORL Dataset, LFW Dataset and Yale Dataset) in similarity index and the minimum distance. The maximum similarity is used to define as the class of query image. The reduction in number of features is achieved by modifying the traditional LBP process.

Conclusion: The proposed modified method is observed as more fast and efficient for face recognition as compared to the existing algorithms.

Cite this article as:

Kumar Manish*, Gupta Rahul, Raju S. Kota and Kumar Dinesh, Modified Local Binary Pattern Algorithm for Feature Dimensionality Reduction, Recent Advances in Computer Science and Communications 2021; 14 (3) . https://dx.doi.org/10.2174/2213275912666190730160705