Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 17 | 02 | Page :
    By

    M.Sirisha,

  • Dr.K.Dasaradha Ramaiah,

  1. Student, Department of Data Sciences, B V Raju Institute of Technology Narsapur, Medak, Telangana, India
  2. 2 Professor& HOD, Department of Data Sciences, B V Raju Institute of Technology Narsapur, Medak, Telangana, India

Abstract

In modern digital signal processing, the capability for denoising and smoothing in real time is very important in scientific, engineering, and industrial applications. This paper presents an efficient hybrid framework that merges two mathematically sound methods, namely, DTT and PDE defined as the Heat Equation, to robustly denoise a signal with minimal distortion. The model addresses one of the most challenging tasks in signal restoration, which maintains the fidelity of structural features while effectively removing the stochastic noise components. The system that is proposed will exploit DTT to make finer-grained local approximation of. expansion of signal behaviour by PDE controlled diffusion in order to. dampen high frequency noises. Other classical linear filters like moving averages. or Gaussian kernels, which are more likely to blur out the details, this combination gives a way to. protect local derivatives and smoothness globally. Application of the algorithm has written in Python 3.11, NumPy to do numerical calculation, and Matplotlib to plot. dynamic visualization. Synthetic sinuoidal signal real-time experiments. additive Gaussian noise corrupted images had shown high SNR and SSIM. improvements. This system used to run at real time (approximately 20 frames per second). thus establishing efficiency in calculations and viable flexibility. The integrated DTT It goes without saying that PDE framework also provides a mathematically interpretable alternative to black-box. filtering as well as a foundation of real-life application in embedded systems, biomedical signal monitoring, IoT sensors and streaming data analytics. Further research can generalize this work to higher dimensions, including the adaptive diffusion coefficients, and parallel implementations on the GPU so as to facilitate scalable performance.

Keywords: Discrete Taylor Transform, Heat Equation, Signal Denoising, PDE, Real-Time Processing, Numerical Diffusion

How to cite this article:
M.Sirisha, Dr.K.Dasaradha Ramaiah. Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach. Current Trends in Signal Processing. 2026; 17(02):-.
How to cite this URL:
M.Sirisha, Dr.K.Dasaradha Ramaiah. Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach. Current Trends in Signal Processing. 2026; 17(02):-. Available from: https://journals.stmjournals.com/ctsp/article=2026/view=246842


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Ahead of Print Subscription Review Article
Volume 17
02
Received 13/06/2026
Accepted 15/06/2026
Published 17/06/2026
Publication Time 4 Days
12

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