Fast Rotation Invariant Thumb Recognition System Using PHT

Problem Definition

Problem Description: Many existing thumb recognition systems are not robust to rotation, leading to issues with accurately identifying individuals when their thumbs are at different angles. This poses a challenge in applications where rotation invariance is crucial, such as biometric security systems or access control. By utilizing the Polar Harmonic Transform (PHT) for rotation invariance, this project aims to address the problem of inaccurate thumb recognition due to varying thumb orientations. The fast computation approach and orthogonal rotation invariance properties of PHTs provide a solution to the numerical instability issues commonly faced in other transform methods, leading to more reliable and accurate thumb recognition systems.

Proposed Work

The proposed work titled "Thumb Recognition System using Polar Harmonic Transform (PHT) for Rotation Invariance" focuses on developing a fast approach for computing Polar Harmonic Transforms (PHTs) using recursion and exploiting the 8-way symmetry/anti-symmetry property of kernel functions. PHTs are orthogonal rotation invariant transforms that offer numerically stable features by utilizing sinusoidal functions in the kernel functions. This project aims to provide a solution to the issue of numerical instability faced by other transformation methods like ZM and PZMs. By recomputing and storing a large part of the computation of PHT kernels, the system can achieve rotation invariance with as little as three multiplications, one addition, and one cosine/sine evaluation per pixel. The implementation will involve three different transforms - Polar Complex Exponential Transform (PCET), Polar Cosine Transform (PCT), and Polar Sine Transform (PST).

Using modules like Regulated Power Supply, Inductive Proximity Sensor, Basic Matlab, and MATLAB GUI, this research falls under the categories of Biomedical Based Projects, Image Processing & Computer Vision, and MATLAB Based Projects, specifically in the subcategories of Image Processing Based Diagnose Projects, Image Classification, and Image Recognition.

Application Area for Industry

The Thumb Recognition System using Polar Harmonic Transform (PHT) for Rotation Invariance project can be applied in various industrial sectors such as biometric security systems, access control systems, healthcare facilities, and even in retail environments. In industries where accurate identification and authentication of individuals are crucial, such as in security systems, the proposed solution of using PHT for rotation invariance can significantly improve the accuracy of thumb recognition systems. This project can also benefit industries using image processing for diagnostics, classification, and recognition tasks, as it provides a fast and numerically stable approach for computing transforms. Specific challenges that industries face, such as inaccurate identification due to thumb rotation and numerical instability issues with existing transform methods, can be effectively addressed by implementing the proposed solution. By utilizing PHTs and their orthogonal rotation invariance properties, industries can achieve more reliable and accurate thumb recognition systems with minimal computational requirements.

Overall, the benefits of implementing this project's solutions include improved security measures, enhanced access control systems, optimized diagnostic processes, and better image classification and recognition capabilities across various industrial domains.

Application Area for Academics

The proposed project on "Thumb Recognition System using Polar Harmonic Transform (PHT) for Rotation Invariance" holds significant relevance and potential applications in research for MTech and PhD students. This project addresses the challenge of inaccurate thumb recognition due to varying orientations by utilizing the Polar Harmonic Transform (PHT) for rotation invariance. The fast computation approach and orthogonal rotation invariance properties of PHTs provide a solution to numerical instability commonly faced in other transform methods, making thumb recognition systems more reliable and accurate. MTech and PhD students in the fields of Biomedical Based Projects, Image Processing & Computer Vision, and MATLAB Based Projects can benefit from this research for innovative research methods, simulations, and data analysis for their dissertation, thesis, or research papers. By exploring the implementation of Polar Complex Exponential Transform, Polar Cosine Transform, and Polar Sine Transform through modules like Regulated Power Supply, Inductive Proximity Sensor, Basic Matlab, and MATLAB GUI, students can pursue research in Image Processing Based Diagnose Projects, Image Classification, and Image Recognition.

The code and literature of this project can serve as a valuable resource for field-specific researchers, MTech students, and PhD scholars to advance their work in image processing and computer vision. The future scope of this project includes further enhancement of thumb recognition systems by integrating advanced algorithms and techniques for more accurate and efficient performance.

Keywords

Image Processing, MATLAB, Mathworks, Biomedical, Body Parameters, Bio Feedback, Computer vision, Image Acquisition, Recognition, Classification, Matching, Neural Network, Neurofuzzy, Classifier, SVM, Linpack, Medical Diagnosis, Cancer detection, Skin problem detection, Opti disk, Thumb Recognition System, Polar Harmonic Transform, Rotation Invariance, Biometric Security Systems, Access Control, Fast Computation, Orthogonal Rotation Invariance, Numerical Instability, Kernel Functions, Recursion, Symmetry/Anti-symmetry, Sinusoidal Functions, Polar Complex Exponential Transform, Polar Cosine Transform, Polar Sine Transform, Regulated Power Supply, Inductive Proximity Sensor, MATLAB GUI.