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I hope this is the correct Stackexchange to ask this question.

I am trying to know : What is the current status of knowledge regarding human vision and pattern recognition.

More specifically,

  1. How does the human eye read signals from the cone cells? Is it row by row, column by column like a computer? or or there other things happening ?
  2. When detecting, say, an edge, or a connected component - does the human eye continue searching row by row? or does it jumpimmediately to the next neighbor? Are human cone cells arranged in arectangular gird with 8 neighbors per cone besides for the edges?(my guess is no). Then how are the neighbors addressed? Does somerace condition occur?

As you can see, I am not a biologist, I am a physicist working with computer vision. I have moderate knowledge of anatomy, but I am willing to learn.

Thank you

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This is a potentially very very broad question, but I'll try to provide a simple answer that addresses the biggest misconceptions.

First of all, animal vision (and brains more generally) is massively parallel. There may be some serial processing steps, but these are also massively parallel. Computers need to digest information into stereotyped operations that can be executed on a CPU. The brain has separate dedicated machinery to each point in space for early vision, so there is no need to process individual "lines" or points in sequence: it all happens at once.

Photoreceptor inputs are converted into center-surround receptive fields in retinal ganglion cells, where light in the center excites and light in the surround suppresses (ON-center cells), or vice versa (OFF-center cells). These receptive fields are then transmitted to thalamus (the lateral geniculate nucleus), and from there to V1, primary visual cortex.

You can then combine many of these circular receptive fields to detect straight edges, like this:

From https://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Perception

The cells in V1 that respond to these "edges" are called "simple cells"; there are also "complex cells" that have more complicated receptive fields, and other sensitivity like to motion and color. Some computer vision strategies end up producing receptive fields that look a lot like the ones found in early visual areas, the earliest ones built out of Gaussian-filtered sin waves.

From V1, there are higher order visual areas that respond to things like shapes, motion, optic flow, etc.

Basic neuroscience textbooks tend to contain a lot of information on the early visual system, Purves Neuroscience is a good example, any edition is fine:

Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. C., LaMantia, A. S., McNamara, J. O., & White, L. E. (2014). Neuroscience, 2008. De Boeck, Sinauer, Sunderland, Mass.

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  • $\begingroup$ In this image, the edge has a particular axis. and thus will detect only one particular edge. Are there then many V1 cells responsible for many axes and sizes in different subfields of the frame of vision? and are the input to the V1 now completely parallel? $\endgroup$ – Sean Sep 10 at 18:26
  • $\begingroup$ i am reading you link - and i will hopefully understand more soon $\endgroup$ – Sean Sep 10 at 18:26
  • $\begingroup$ @Sean Yes. Many orientations, spatial scales, etc. There are lots more in the area responsible for the fovea, peripheral vision is more vague. $\endgroup$ – Bryan Krause Sep 10 at 18:28
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    $\begingroup$ @Sean I'd recommend starting with a basic neuroscience textbook; vision is often used as a model system in neurobiology and these texts have extensive sections on vision. Purves' "Neuroscience" or Kandel's "Principles of Neural Science" are good choices. Even Wikipedia is okay for background. For the visual processing hierarchy, Felleman & Van Essen 1991 is probably the canonical reference. $\endgroup$ – Bryan Krause Sep 10 at 19:20
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    $\begingroup$ The lecture notes I linked above from the University of Colorado are also a good intro. $\endgroup$ – Bryan Krause Sep 10 at 19:22

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