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Search Results (21)
  • Open Access


    Detection of Fuel Adulteration Using Wave Optical with Machine Learning Algorithms

    S. Dilip Kumar1,*, T. V. Sivasubramonia Pillai2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 19-33, 2022, DOI:10.32604/csse.2022.019366

    Abstract Fuel is a very important factor and has considerable influence on the air quality in the environment, which is the heart of the world. The increase of vehicles in lived-in areas results in greater emission of carbon particles in the environment. Adulterated fuel causes more contaminated particles to mix with breathing air and becomes the main source of dangerous pollution. Adulteration is the mixing of foreign substances in fuel, which damages vehicles and causes more health problems in living beings such as humans, birds, aquatic life, and even water resources by emitting high levels of hydrocarbons, nitrogen oxides, and carbon… More >

  • Open Access


    Image Authenticity Detection Using DWT and Circular Block-Based LTrP Features

    Marriam Nawaz1, Zahid Mehmood2,*, Tahira Nazir1, Momina Masood1, Usman Tariq3, Asmaa Mahdi Munshi4, Awais Mehmood1, Muhammad Rashid5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1927-1944, 2021, DOI:10.32604/cmc.2021.018052

    Abstract Copy-move forgery is the most common type of digital image manipulation, in which the content from the same image is used to forge it. Such manipulations are performed to hide the desired information. Therefore, forgery detection methods are required to identify forged areas. We have introduced a novel method for features computation by employing a circular block-based method through local tetra pattern (LTrP) features to detect the single and multiple copy-move attacks from the images. The proposed method is applied over the circular blocks to efficiently and effectively deal with the post-processing operations. It also uses discrete wavelet transform (DWT)… More >

  • Open Access


    Digital Forensics for Skulls Classification in Physical Anthropology Collection Management

    Imam Yuadi1,*, Myrtati D. Artaria2, Sakina3, A. Taufiq Asyhari4

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3979-3995, 2021, DOI:10.32604/cmc.2021.015417

    Abstract The size, shape, and physical characteristics of the human skull are distinct when considering individual humans. In physical anthropology, the accurate management of skull collections is crucial for storing and maintaining collections in a cost-effective manner. For example, labeling skulls inaccurately or attaching printed labels to skulls can affect the authenticity of collections. Given the multiple issues associated with the manual identification of skulls, we propose an automatic human skull classification approach that uses a support vector machine and different feature extraction methods such as gray-level co-occurrence matrix features, Gabor features, fractal features, discrete wavelet transforms, and combinations of features.… More >

  • Open Access


    A Triple-Channel Encrypted Hybrid Fusion Technique to Improve Security of Medical Images

    Ahmed S. Salama1,2,3, Mohamed Amr Mokhtar3, Mazhar B. Tayel3, Esraa Eldesouky4,6, Ahmed Ali5,6,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 431-446, 2021, DOI:10.32604/cmc.2021.016165

    Abstract Assuring medical images protection and robustness is a compulsory necessity nowadays. In this paper, a novel technique is proposed that fuses the wavelet-induced multi-resolution decomposition of the Discrete Wavelet Transform (DWT) with the energy compaction of the Discrete Wavelet Transform (DCT). The multi-level Encryption-based Hybrid Fusion Technique (EbhFT) aims to achieve great advances in terms of imperceptibility and security of medical images. A DWT disintegrated sub-band of a cover image is reformed simultaneously using the DCT transform. Afterwards, a 64-bit hex key is employed to encrypt the host image as well as participate in the second key creation process to… More >

  • Open Access


    Multimodal Medical Image Registration and Fusion for Quality Enhancement

    Muhammad Adeel Azam1, Khan Bahadar Khan2,*, Muhammad Ahmad3, Manuel Mazzara4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 821-840, 2021, DOI:10.32604/cmc.2021.016131

    Abstract For the last two decades, physicians and clinical experts have used a single imaging modality to identify the normal and abnormal structure of the human body. However, most of the time, medical experts are unable to accurately analyze and examine the information from a single imaging modality due to the limited information. To overcome this problem, a multimodal approach is adopted to increase the qualitative and quantitative medical information which helps the doctors to easily diagnose diseases in their early stages. In the proposed method, a Multi-resolution Rigid Registration (MRR) technique is used for multimodal image registration while Discrete Wavelet… More >

  • Open Access


    Improving Reconstructed Image Quality via Hybrid Compression Techniques

    Nancy Awadallah Awad1,*, Amena Mahmoud2

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3151-3160, 2021, DOI:10.32604/cmc.2021.014426

    Abstract Data compression is one of the core fields of study for applications of image and video processing. The raw data to be transmitted consumes large bandwidth and requires huge storage space as a result, it is desirable to represent the information in the data with considerably fewer bits by the mean of data compression techniques, the data must be reconstituted very similarly to the initial form. In this paper, a hybrid compression based on Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) is used to enhance the quality of the reconstructed image. These techniques are followed by entropy encoding such… More >

  • Open Access


    Discrete Wavelet Transmission and Modified PSO with ACO Based Feed Forward Neural Network Model for Brain Tumour Detection

    Machiraju Jayalakshmi1, *, S. Nagaraja Rao2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710

    Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and a feed-forward neural network (FNN)… More >

  • Open Access


    Balanced GHM Mutiwavelet Transform Based Contrast Enhancement Technique for Dark Images Using Dynamic Stochastic Resonance

    S. Deivalakshmi*, P. Palanisamy1, X. Z. Gao2

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 459-471, 2019, DOI:10.31209/2018.100000001

    Abstract The main aim of this paper is to propose a new technique for enhancing the contrast of dark images using Dynamic Stochastic Resonance (DSR) and Multi Wavelet Transform (MWT), which is computationally more efficient than the conventional methods. In the work, for enhancing the contrast of dark images, the intrinsic noise (darkness) of dark images has been used. The proposed MWT-based DSR scheme (MWT-DSR) can yield better performances in terms of visual information and color preservation than already reported techniques. The desired output response is validated by the Relative Contrast Enhancement Factor (F), Perceptual Quality Measures (PQM) and Color Enhancement… More >

  • Open Access


    Use of Discrete Wavelet Features and Support Vector Machine for Fault Diagnosis of Face Milling Tool

    C. K. Madhusudana1, N. Gangadhar1, Hemantha Kumar, Kumar,*,1, S. Narendranath1

    Structural Durability & Health Monitoring, Vol.12, No.2, pp. 111-127, 2018, DOI: 10.3970/sdhm.2018.01262

    Abstract This paper presents the fault diagnosis of face milling tool based on machine learning approach. While machining, spindle vibration signals in feed direction under healthy and faulty conditions of the milling tool are acquired. A set of discrete wavelet features is extracted from the vibration signals using discrete wavelet transform (DWT) technique. The decision tree technique is used to select significant features out of all extracted wavelet features. C-support vector classification (C-SVC) and ν-support vector classification (ν-SVC) models with different kernel functions of support vector machine (SVM) are used to study and classify the tool condition based on selected features.… More >

  • Open Access


    A Robust Image Watermarking Scheme Using Z-Transform, Discrete Wavelet Transform and Bidiagonal Singular Value Decomposition

    N. Jayashree1,*, R. S. Bhuvaneswaran1

    CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 263-285, 2019, DOI:10.32604/cmc.2019.03924

    Abstract Watermarking is a widely used solution to the problems of authentication and copyright protection of digital media especially for images, videos, and audio data. Chaos is one of the emerging techniques adopted in image watermarking schemes due to its intrinsic cryptographic properties. This paper proposes a new chaotic hybrid watermarking method combining Discrete Wavelet Transform (DWT), Z-transform (ZT) and Bidiagonal Singular Value Decomposition (BSVD). The original image is decomposed into 3-level DWT, and then, ZT is applied on the HH3 and HL3 sub-bands. The watermark image is encrypted using Arnold Cat Map. BSVD for the watermark and transformed original image… More >

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