Leveraging Mutual Information in Local Descriptions: From Local Binary Patterns to the Image

Syed, Tahir Q.; Behlim, Sadaf I.; Merchant, Alishan; Thomas, Alexis; Khan, Furqan

doi:10.1007/978-3-319-23234-8_23

Cited by 2 publications

(1 citation statement)

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“…Summarizing local image content is considered a fundamental step in all classical computer vision tasks such as object detection and recognition [3,8], texture analysis [11], motion analysis [2,11], image restoration and reconstruction [6] etc. This step usually involves extraction of low level features such as finding out where the edges are, detecting interest points and their region of interests by applying local neighborhood operations.…”

Section: Introductionmentioning

confidence: 99%

Z-Images

Vigneron¹,

Syed²,

Duarte³

et al. 2017

Pattern Recognition and Image Analysis

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Local patterns and other patch based features have been an integral part of various computer vision applications as they encode local structural and statistical information. In this paper, we propose an image coding technique that utilizes Zeckendorf representation of pixel intensities and basic mathematical operators such as intersection, set difference, maximum, summation etc. for summarization of image regions. The algorithm produces a Z-coded image that tells about the homogeneity or the contrast in image regions with all codes in a range of 0 to 255.Vigneron-This research was supported by the program Cátedras Franco-Brasileiras no Estado de São Paulo, an initiative of the French consulate and the state of São Paulo (Brazil). We thank our colleagues Prof. João M.T. Romano, Dr. Kenji Nose and Dr. Michele Costa, who provided insights that greatly assisted this work.

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