The statistics of lines in natural images and implications for visual detection |
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| Authors: | Ha Youn Lee |
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| Institution: | a Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14618, United States
b Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, United States |
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| Abstract: | As borders between different regions, lines are an important element of natural images. Already at the level of the mammalian primary visual cortex (V1), neurons respond best to oriented bars. We reduce a set of images to linear segments and analyze their statistical properties. In particular, appropriately defined Fourier spectra show more power in their transverse component than in the longitudinal one. We then characterize filters that are best suited for extracting information from such images, and find some qualitative consistency with neural connections in V1. We also demonstrate that such filters are efficient in reconstructing missing lines in an image. |
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| Keywords: | Primary visual cortex (V1) Neurons Nature image analysis Fiters for visual detections |
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