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

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

Biomimetics (Basel)

College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China.

Published: July 2024

AI Article Synopsis

  • - The concept of Image Phase Congruency (IPC) is crucial for how our visual system processes spatial frequency information, enhancing our ability to recognize objects, textures, and spatial relationships in varying lighting conditions.
  • - IPC remains effective despite changes in contrast and illumination because it focuses on the relative phase of light waves, which helps maintain consistent feature detection across different environments.
  • - The survey covers biological studies on IPC, its mathematical and computational frameworks, its diverse applications in computer vision (such as object detection and image segmentation), and the current challenges and future improvements needed in its practical use.

Article Abstract

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11274423PMC
http://dx.doi.org/10.3390/biomimetics9070422DOI Listing

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