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Optimal directional texture codes using multiscale bit crossover count planes for palmprint recognition

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Abstract

The single variance Gabor filters have widely been employed for palmprint structural representation. These filters display inefficient representation due to loss in information detection and false localization of diverse width palmlines. Therefore, the proposed work employs a multiscale filtering based representation, “optimal directional texture codes (ODTC)”. The proposed representation make use of the line structures that go unnoticed with single variance Gabor filters and the multiscale bit crossover count (MBCC) scheme integrates these structural attributes of multiple width. Firstly, the MBCC planes are obtained using bit transition count across the strings which are formed by concatenating the binarized responses of the Gabor filter coefficients at corresponding location binary responses in considered orientations. Thereafter, optimal directional texture plane, i.e., directional representation (DR), is derived by computing dominant directional indices associated with the maximum value of MBCC at each corresponding locations of MBCC planes in different directions. Finally, encoding of the obtained DR results in final ODTC representation. The experimental results on, standard PolyU 2D, multispectral and IITD touchless palmprint databases, demonstrate that the proposed work outperforms several state-of-the-art coding based approaches.

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Authors and Affiliations

  1. Madhav Institute of Technology & Science, Gwalior, MP- 474005, India

    Pawan Dubey

  2. National Institute of Technology Delhi Narela, Delhi, 110040, India

    Tirupathiraju Kanumuri

  3. Lancaster University, Lancaster, UK

    Ritesh Vyas

Authors
  1. Pawan Dubey
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  2. Tirupathiraju Kanumuri
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  3. Ritesh Vyas
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Correspondence to Pawan Dubey.

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Appendix:: Gabor filters

Appendix:: Gabor filters

The Gabor filters can be defined as (8):

$$ \begin{array}{ll} G(x,y,\sigma ,u,\theta ) &= \frac{1}{{2\pi {\sigma^{2}}}}\exp \left( {\frac{{ - \left( {\left[ {\begin{array}{*{20}{c}} x&y \end{array}} \right] \cdot {{\left[ {\begin{array}{*{20}{c}} x&y \end{array}} \right]}^{T}}} \right)}}{{2{\sigma^{2}}}}} \right)\\ &\bullet \exp \left( {2\pi iu\left[ {\begin{array}{*{20}{c}} x&{ y} \end{array}} \right] \cdot \left[ {\begin{array}{*{20}{c}} {\cos \theta }\\ {\sin \theta }, \end{array}} \right]} \right) \end{array} $$
(8)

here, “⋅” represents matrix multiplication, \(i=\sqrt {-1}\); u represents complex sinusoidal grating frequency;, σ is the variance of 2-D Gaussian envelope; and orientation of sinusoidal gratings is represented by 𝜃 within the range bounded to [0∘ 180∘]. The particular orientation, 𝜃l, belongs to this set is obtained as:

$$ {\theta_{l} = (l - 1) \times \frac{{180}}{N}} , l = 1, 2, 3 , {\ldots} N $$
(9)

Thus, Gabor filter, \(G_{{\sigma _{j}}}^{{\theta _{l}}}\) with multi-scale, σj and multi orientation, 𝜃l, can be designed as:

$$ \begin{array}{ll} G_{{\sigma_{j}}}^{{\theta_{l}}}(x,y,{\sigma_{j}},u,{\theta_{l}}) &= \frac{1}{{2\pi {\sigma_{j}^{2}}}}\exp \left( {\frac{{ - \left( {\left[ {\begin{array}{*{20}{c}} x&y \end{array}} \right]) \cdot {{\left[ {\begin{array}{*{20}{c}} x&y \end{array}} \right]}^{T}}} \right)}}{{2{\sigma_{j}^{2}}}}} \right)\\ &\bullet \exp \left( {2\pi iu\left[ {\begin{array}{*{20}{c}} x&y \end{array}} \right] \cdot \left[ {\begin{array}{*{20}{c}} {\cos {\theta_{l}}}\\ {\sin {\theta_{l}}} \end{array}} \right]} \right) \end{array} $$
(10)

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Dubey, P., Kanumuri, T. & Vyas, R. Optimal directional texture codes using multiscale bit crossover count planes for palmprint recognition. Multimed Tools Appl 81, 20291–20310 (2022). https://doi.org/10.1007/s11042-022-12580-1

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