Developing digital signal clustering method using local binary pattern histogram

Rasras, Rashad J.; Zahran, Bilal; Sara, Mutaz Rasmi Abu; Alqadi, Ziad

doi:10.11591/ijece.v11i1.pp872-878

Cited by 6 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The face detection process starts with image capture, loading, and conversion to grayscale. The Haar cascade classifier is then used to detect faces, categorizing images as positive (with a face) or negative (without a face) [22]. This classification relies on a trained classifier that determines if a new image is positive or negative based on a dataset of face and non-face images.…”

Section: Face Detection and Face Recognitionmentioning

confidence: 99%

Streamlining Attendance Management in Education: A Web-Based System Combining Facial Recognition and QR Code Technology

Emily Sing Kiang Siew,

Zhi Yan Chong,

Sah Nah Sze

et al. 2023

ARASET

View full text Add to dashboard Cite

Attendance tracking has long posed challenges in educational institutions due to the inefficiency and error-prone nature of traditional paper-based methods. In response, many institutions have embraced web technologies and automated attendance systems, incorporating biometrics, QR codes, barcodes, and RFID-based technologies. However, the applicability of these systems may vary across different educational settings. This paper introduces a web-based student attendance management system that combines facial recognition technology and QR codes to address the challenges associated with manual attendance tracking in a university college. The system leverages a centralized database for streamlined monitoring and auditing of attendance records, offering the flexibility to choose between face recognition and QR code attendance marking options. User acceptance tests were conducted to evaluate the system's effectiveness, and the results indicate that the proposed system greatly improves attendance tracking transparency and demonstrates high usability based on positive user ratings. Additionally, the preference for face recognition over QR code scanning was evident. Incorporating these technologies into the automated attendance system represents a substantial advancement in educational technology, offering an accurate and efficient way of recording attendance.

show abstract

Section: Face Detection and Face Recognitionmentioning

confidence: 99%

Streamlining Attendance Management in Education: A Web-Based System Combining Facial Recognition and QR Code Technology

Emily Sing Kiang Siew,

Zhi Yan Chong,

Sah Nah Sze

et al. 2023

ARASET

View full text Add to dashboard Cite

show abstract

“…6) The cover image is sourced, and its dimensions are ascertained. (7) The cover image undergoes reshaping into a single-row matrix.…”

Section: Proposed Ulsb2 Steganographic Techniquementioning

confidence: 99%

“…It has been asserted that successful decryption can only transpire if the decryption key is available to the receiver. Parallelly, steganography is characterised as the act of covertly embedding a secret message within a cover file, ensuring its presence remains wholly obscured [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…In scenarios invoking cryptography, it is possible for third parties to discern the occurrence of a communication, though the content remains encrypted and thus, unintelligible. Conversely, with steganography, any external observer remains oblivious to the presence of covert data or the occurrence of clandestine communication, owing to the profound concealment effected by an intermediary [1][2][3][4][5][6][7]. This study's emphasis has been placed on safeguarding secret messages harbouring confidential data during its transmission over communication channels, with the ultimate aim to reinforce both the privacy and integrity of said data.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhanced Efficiency and Security in LSB2 Steganography: Burst Embedding and Private Key Integration

Rasras,

Sara,

Alqadi

2023

View full text Add to dashboard Cite

In the realm of digital colour image steganography, the utilisation of an image key for the extraction of essential covering stego-bytes from predetermined secret positions was explored. The traditional Least Significant Bit (LSB) and LSB2 methodologies were streamlined by substituting the logical operations within both the hiding and extraction functions with straightforward assignment operations. An enhancement was introduced to the LSB2 steganographic methods for secret message conveyance without compromising data hiding capacity. Instead of the conventional character-by-character embedding seen in the LSB2 method, the binary code of the concealed message was embedded in a burst manner within the covering image. Similarly, the extraction from the stego image was conducted in a burst fashion, leading to a reduction in the processes required for both data hiding and extraction. As a result, shorter hiding and extraction durations were achieved, culminating in augmented data steganography throughput. For bolstering message security against potential breaches, the proposed ULSB2 method integrated a confidential private key (PK) composed of two double values. This key provisioned the necessary key space to deter hacking endeavours. A comparative analysis was conducted between the outcomes derived from the ULSB2 method and those of prevailing techniques to delineate the enhancements in both quality and speed of message steganography.

show abstract

“…Speech signal [1,2] is a set of samples, each of them represents the amplitude value for the corresponding analogue value sampled and quantized at a period of time, this signal can be represented by a one column matrix (mono speech) or two column matrix (stereo speech), these matrices can be easily maintained to apply a necessary operation using the speech signal [3][4][5] .…”

Section: Introductionmentioning

confidence: 99%

Window method for digital speech files cryptography

2021

jecet

View full text Add to dashboard Cite

Speech signals some time require encryption to secure them from the hacker, in this article research a simple, and easy to implement method of digital speech file cryptography will be introduced. The suggested window method will be implemented to prove that the method satisfies the requirements of cryptography by giving good values of the quality parameters after the encryption and decryption. The introduced method will be compared with DES method to show how the proposed method will increase the efficiency and cryptography throughput.

show abstract

Developing digital signal clustering method using local binary pattern histogram

Cited by 6 publications

References 12 publications

Streamlining Attendance Management in Education: A Web-Based System Combining Facial Recognition and QR Code Technology

Streamlining Attendance Management in Education: A Web-Based System Combining Facial Recognition and QR Code Technology

Enhanced Efficiency and Security in LSB2 Steganography: Burst Embedding and Private Key Integration

Window method for digital speech files cryptography

Contact Info

Product

Resources

About