COMPUTATIONLESS PALM-PRINT VERIFICATION USING WAVELET ORIENTED ZERO-CROSSING SIGNATURE

Palmprints can be characterized by their texture and the patterns of that texture dominate in a vertical direction. Therefore, the energy of the coefficients in the transform domain is more concentrated in the vertical sideband. Using this idea, this paper proposes the characterization of the texture features of the palmprint using zero-crossing signatures based on the dyadic discrete wavelet transform (DWT) to effectively identify an individual. A zero-crossing signature of 4 x 256 was generated from the lower four resolution levels of dyadic DWT in the enrolment process and stored in the database to identify the person in recognition mode. Euclidean distance was determined to find the best fit for query palmprints zero-crossing signature from the dataset. The proposed algorithm was tested on the PolyU dataset containing 6000 multi-spectral images. The proposed algorithm achieved 96.27% accuracy with a lower recognition time of 0.76 seconds. ABSTRAK: Pengesan Tapak Tangan boleh dikategorikan berdasarkan ciri-ciri tekstur dan corak pada tekstur yang didominasi pada garis tegak. Oleh itu, pekali tenaga di kawasan transformasi adalah lebih penuh pada jalur-sisi menegak. Berdasarkan idea ini, cadangan kajian ini adalah berdasarkan ciri-ciri tekstur pada tapak tangan dan tanda pengenalan sifar-silang melalui transformasi gelombang kecil diadik yang diskret (DWT) bagi mengecam individu. Pada mod pengecaman, tanda pengenalan sifar-silang 4 x 256 yang terhasil daripada tahap diadik resolusi empat terendah DWT digunakan dalam proses kemasukan dan simpanan di pangkalan data bagi mengenal pasti individu. Jarak Euklidan yang terhasil turut digunakan bagi memperoleh padanan tapak tangan paling sesuai melalui tanda pengenalan sifar-silang dari set data. Algoritma yang dicadangkan ini diuji pada set data PolyU yang mengandungi 6000 imej pelbagai-spektrum. Algoritma yang dicadangkan ini berjaya mencapai ketepatan sebanyak 96.27% dengan durasi pengecaman berkurang sebanyak 0.76 saat.

A New Blind Source Separation Algorithm Framework for Noisy Mixing Model Based on the Energy Concentration Characteristic in Signal Transform Domain

Blind source separation is a widely used technique to analyze multichannel data. In most real-world applications, noise is inevitable and will affect the quality of signal separation and even make signal separation failure. In this paper, a new signal processing framework is proposed to separate noisy mixing sources. It is composed of two different stages. The first step is to process the mixing signal by a certain signal transform method to make the expected signals have energy concentration characteristics in the transform domain. The second stage is formed by a certain BSS algorithm estimating the demixing matrix in the transform domain. In the energy concentration segment, the SNR can reach a high level so that the demixing matrix can be estimated accurately. The analysis process of the proposed algorithm framework is analyzed by taking the wavelet transform as an example. Numerical experiments demonstrate the efficiency of the proposed algorithm to estimate the mixing matrix in comparison with well-known algorithms.

Research on High Robust Multimedia Image Encryption Based on Gyrator Transform Domain Model

The encryption and privacy protection of multimedia image resources are of great value in the information age. The utilization of the gyrator transform domain model in multimedia image encryption can select parameters more accurately, so it has a wider scope of utilization and further ameliorates the stability of the whole system. On account of this, this paper first analyzes the concept and connotation of gyrator transform, then studies the image encryption algorithm on account of gyrator transform, and verifies the robustness of the gyrator transform algorithm under the influence of noise interference, shear attack, and other factors through the high robust multimedia image encryption and result analysis of gyrator transform.

Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain

Multimedia data in various forms is now readily available because of the widespread usage of Internet technology. Unauthorized individuals abuse multimedia material, for which they should not have access to, by disseminating it over several web pages, to defraud the original copyright owners. Numerous patient records have been compromised during the surge in COVID-19 incidents. Adding a watermark to any medical or defense documents is recommended since it protects the integrity of the information. This proposed work is recognized as a new unique method since an innovative technique is being implemented. The resilience of the watermarked picture is quite crucial in the context of steganography. As a result, the emphasis of this research study is on the resilience of watermarked picture methods. Moreover, the two-stage authentication for watermarking is built with key generation in the section on robust improvement. The Fast Fourier transform (FFT) is used in the entire execution process of the suggested framework in order to make computing more straightforward. With the Singular Value Decomposition (SVD) accumulation of processes, the overall suggested architecture becomes more resilient and efficient. A numerous quality metrics are utilized to find out how well the created technique is performing in terms of evaluation. In addition, several signal processing attacks are used to assess the effectiveness of the watermarking strategy.