Astroid shaped DCT feature extraction for enhanced face recognition

Divya, R.; Rath, Anwesha; Ramachandran, S.; Manikantan, K.

doi:10.1145/2381716.2381735

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Author defined the quantitative assessment on the facial distortion so that the quality evaluation will be performed effectively. Divya R. [12] has defined DCT based feature extraction approach to improve the facial recognition process. Author improved the recognition process under shape analysis approach.…”

Section: Existing Workmentioning

confidence: 99%

An Occluded Face Recognition Approach using Feature Specific KPCA Approach

Sharma¹,

Kumar²

2014

Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies

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Facial Recognition is having many challenges along with the application. One of such challenge is facial expression recognition. In this work, feature analysis based hybrid architecture is defined to perform facial expression recognition. The work is divided in two main stags. First to recognize the face itself and later on the recognition of facial expression is performed. In this paper, the feature analysis is performed based on Gabor filter analysis. Once the featured dataset is generated, the recognition is performed using probabilistic neural network and the KPCA approach. The Weighted Eigen distance threshold based analysis is performed to recognize the face as well as the expression. The obtained result shows the accurate detection of face and the expression.

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Section: Existing Workmentioning

confidence: 99%

An Occluded Face Recognition Approach using Feature Specific KPCA Approach

Sharma¹,

Kumar²

2014

Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies

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“…Such capturing results partial capturing [7], pose variation, facial information loss [8] etc. Subject specific variations and data loss requires a series of filter [9,10] operation to repair image even then it will impact similarity score. The classified facial mapping process can be applied to represent the entire face recognition process.…”

Section: Introductionmentioning

confidence: 99%

MFAST Processing Model for Occlusion and Illumination Invariant Facial Recognition

Juneja¹

2016

Advanced Computing and Communication Technologies

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Illumination Variation and wearable objects loses the partial facial information that it degrades the accuracy of recognition process. In this paper, a high performance driven accurate method is provided for facial recognition. The proposed MFAST (Multi-Featured Analog Signal Transformed) Model genuinely transmute the substantial facial information in analog featured conformation. This analog featured structured is formed using segmented featured elicitation. These features include center difference evaluation as moment, the asymmetric structure analysis as Skewness and Outlier Prone Measure as Kurtosis. These analogous features are shaped to justified form and generate a compound signal form. Mapping of these distillates signal points over facial dataset with specification of threshold window. The decomposed form recognition method enhanced the accuracy and performance. The experimentation on FERET, LFW and Indian Databases signify that the model outperformed than existing algorithms.

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Overview on Binary Optimization Using Swarm-Inspired Algorithms

et al. 2021

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Swarm Intelligence is applied to optimisation problems due to its robustness, scalability, generality, and flexibility. Based on simple rules, simple reactive agents -swarm (e.g. fish, bird, and ant)directly or indirectly exchange information to find an optimal solution. Among multiple nature inspirations and versions, the dilemma of choosing proper swarm-based algorithms for each type of problem prevents their recurrent application. This scenario gets even more challenging when considering binary optimisation because of the absence of overview papers that assembles the trends, benefits and limitations of swarmbased techniques. Based on 403 scientific papers, we describe the basis of the leading binary swarm-based algorithms presenting their rationales, equations, pseudocodes, and descriptions of their applications to tackle this research gap. We also define a new classification based on the mechanism to update the solutions and the displacements, indicating that the Binary-Binary approach -binary decision variables and binary search space -is more efficient for binary optimisation in accuracy and computational cost.

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Astroid shaped DCT feature extraction for enhanced face recognition

Cited by 4 publications

References 16 publications

An Occluded Face Recognition Approach using Feature Specific KPCA Approach

An Occluded Face Recognition Approach using Feature Specific KPCA Approach

MFAST Processing Model for Occlusion and Illumination Invariant Facial Recognition

Overview on Binary Optimization Using Swarm-Inspired Algorithms

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