Multi-focus Image Fusion Framework Using Total Variation and Phase Congruency

Mei, Jiatian; Nie, Rencan; Zhou, Dongming; Liu, Dong

doi:10.1109/compcomm.2018.8781019

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…The system accuracy is computed at equal error rate (EER) value which reflects the maximum system performance when the false acceptance rate (FAR) equals to the false rejection rate (FRR) as explained in 15. The error distance between x ̅ and y ̅ with m+1 length can be described in (16)(17)(18) [30][31][32][33][34].…”

Section: Classificationmentioning

confidence: 99%

Towards better performance: phase congruency based face recognition

Hamd

Rasool

2020

TELKOMNIKA

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Phase congruency is an edge detector and measurement of the significant feature in the image. It is a robust method against contrast and illumination variation. In this paper, two novel techniques are introduced for developing a low-cost human identification system based on face recognition. Firstly, the valuable phase congruency features, the gradient-edges and their associated angles are utilized separately for classifying 130 subjects taken from three face databases with the motivation of eliminating the feature extraction phase. By doing this, the complexity can be significantly reduced. Secondly, the training process is modified when a new technique, called averaging-vectors is developed to accelerate the training process and minimizes the matching time to the lowest value. However, for more comparison and accurate evaluation, three competitive classifiers: Euclidean distance (ED), cosine distance (CD), and Manhattan distance (MD) are considered in this work. The system performance is very competitive and acceptable, where the experimental results show promising recognition rates with a reasonable matching time.

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Section: Classificationmentioning

confidence: 99%

Towards better performance: phase congruency based face recognition

Hamd

Rasool

2020

TELKOMNIKA

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Progress of Image Fusion in the Digital Era: A Comprehensive Survey of Techniques, Applications, and Future Directions

Soniminde

Biradar

2023

Preprint

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Biological Basis and Computer Vision Applications of Image Phase Congruency: A Comprehensive Survey

Tian,

Wen,

et al. 2024

Biomimetics

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The concept of Image Phase Congruency (IPC) is deeply rooted in the way the human visual system interprets and processes spatial frequency information. It plays an important role in visual perception, influencing our capacity to identify objects, recognize textures, and decipher spatial relationships in our environments. IPC is robust to changes in lighting, contrast, and other variables that might modify the amplitude of light waves yet leave their relative phase unchanged. This characteristic is vital for perceptual tasks as it ensures the consistent detection of features regardless of fluctuations in illumination or other environmental factors. It can also impact cognitive and emotional responses; cohesive phase information across elements fosters a perception of unity or harmony, while inconsistencies can engender a sense of discord or tension. In this survey, we begin by examining the evidence from biological vision studies suggesting that IPC is employed by the human perceptual system. We proceed to outline the typical mathematical representation and different computational approaches to IPC. We then summarize the extensive applications of IPC in computer vision, including denoise, image quality assessment, feature detection and description, image segmentation, image registration, image fusion, and object detection, among other uses, and illustrate its advantages with a number of examples. Finally, we discuss the current challenges associated with the practical applications of IPC and potential avenues for enhancement.

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Multi-focus Image Fusion Framework Using Total Variation and Phase Congruency

Cited by 3 publications

References 15 publications

Towards better performance: phase congruency based face recognition

Towards better performance: phase congruency based face recognition

Progress of Image Fusion in the Digital Era: A Comprehensive Survey of Techniques, Applications, and Future Directions

Biological Basis and Computer Vision Applications of Image Phase Congruency: A Comprehensive Survey

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