DOI: 10.14704/nq.2018.16.3.1185

A Visual Coding Method for Geographic Statistics Based on the Pattern Recognition Feature of Optic Nerve in Cerebral Cortex

Zuofei Tan, Zhaoxia Wang, Shenglin Li, Qinghui Ren, Bo Song


The human visual system can easily identify a variety of objects, all thanks to its powerful pattern recognition capability. One theory holds that the brain’s visual recognition mechanism is mainly achieved by single neurons and complex neurons located in area V1 of the cerebral cortex. Both types of cells decompose and synthesize the visual signals from sensory organs to extract their pattern features (Riesnhuber et al., 1991). However, in the information visualization field where logic is quite complicated, the visual recognition system of human beings has great limitations and can only effectively recognize complex visual patterns after the complex information is pretreated by a set of scientific visual coding methods. In the context of geographic statistics, based on the single neurons and complex neurons model and Gestalt psychology, this paper proposes a visual coding method based on aggregation and subdivision (AS method) to visualize geographic statistics. The simulation test results show that the AS method can deliver a good mapping relationship between geographic locations and a good rectangular aspect ratio and thus can achieve high visual perception efficiency.


Visual Cortex, Pattern Recognition, Single Neurons and Complex Neurons Model, Gestalt Psychology, Visual Coding, Cartogram, Tree graph

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Aaron K, Flight Patterns, 2006. (Accessed on 18 June, 2017).

Anita G. Mapping Density with Hexagonal Grids. (Accessed on 02 October, 2012).

Curtis AJ, Mills JW, Leitner M. Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina. International Journal of Health Geographics 2006; 5(1): 44-55.

Evans DC. Gestalt Perception. Bottlenecks. Apress 2017.

Forster F. Use of a demographic base map for the presentation of areal data in epidemiology. British Journal of Preventive & Social Medicine 1966;20(4):165-71.

Gastner MT, Shalizi CR, Newman ME. Maps and cartograms of the 2004 US presidential election results. Advances in Complex Systems 2005;8(01):117-23.

Ghoniem M, Cornil M, Broeksema B, Stefas M, Otjacques B. Weighted maps: treemap visualization of geolocated quantitative data. In Visualization and Data Analysis 2015. International Society for Optics and Photonics 2015; 9397: 93970G.

Hubel DH, Wiesel TN. Receptive fields of single neurones in the cat's striate cortex. Journal of Physiology 1959; 148(3):574-91.

IBM trademark., 2017.

Kanwisher N, Wojciulik E. Visual attention: insights from brain imaging. Nature Reviews Neuroscience 2000; 1(2): 91-100.

Keim ED, Kohlhammer J, Ellis G. Mastering the Information Age: Solving Problems with Visual Analytics, Eurographics Association, 2010.

Liu Z, Jiang B, Heer J. imMens: Real‐time Visual Querying of Big Data. Computer Graphics Forum 2013;32(3):421–30.

Munzner T. Visualization Analysis and Design. Wiley Interdisciplinary Reviews Computational Statistics 2015; 2(4):387–403.

Nadieh B. Urbanization in East Asia. (Accessed on 08 February, 2015).

Riesenhuber M, Poggio T. Models of object recognition. Current Opinion in Neurobiology 1991;1(2):270-73.

Serre T, Wolf L, Poggio T. Object recognition with features inspired by visual cortex. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society 2005:994-1000.

Ward MO, Grinstein G, Keim D. Interactive data visualization: foundations, techniques, and applications. CRC Press, 2010;51(4):188-95. on 28 February, 2016). (Accessed on 08 February, 2014).

Yang HB. Study of Edge Bundling based on Edge Clustering. Shenzhen University 2016:40-48.

Supporting Agencies

This work was supported by the project of Facility Asset Visualization and Decision Analysis System under No. AS214R002. We thank the anonymous reviewers whose comments helped improve the manuscript.

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