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Search Results (17)
  • Open Access

    ARTICLE

    Face Age Estimation Based on CSLBP and Lightweight Convolutional Neural Network

    Yang Wang1, Ying Tian1,*, Ou Tian2

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2203-2216, 2021, DOI:10.32604/cmc.2021.018709

    Abstract As the use of facial attributes continues to expand, research into facial age estimation is also developing. Because face images are easily affected by factors including illumination and occlusion, the age estimation of faces is a challenging process. This paper proposes a face age estimation algorithm based on lightweight convolutional neural network in view of the complexity of the environment and the limitations of device computing ability. Improving face age estimation based on Soft Stagewise Regression Network (SSR-Net) and facial images, this paper employs the Center Symmetric Local Binary Pattern (CSLBP) method to obtain the feature image and then combines… More >

  • Open Access

    ARTICLE

    A Secure Rotation Invariant LBP Feature Computation in Cloud Environment

    Shiqi Wang1, Mingfang Jiang2,*, Jiaohua Qin1, Hengfu Yang2, Zhichen Gao3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2979-2993, 2021, DOI:10.32604/cmc.2021.017094

    Abstract In the era of big data, outsourcing massive data to a remote cloud server is a promising approach. Outsourcing storage and computation services can reduce storage costs and computational burdens. However, public cloud storage brings about new privacy and security concerns since the cloud servers can be shared by multiple users. Privacy-preserving feature extraction techniques are an effective solution to this issue. Because the Rotation Invariant Local Binary Pattern (RILBP) has been widely used in various image processing fields, we propose a new privacy-preserving outsourcing computation of RILBP over encrypted images in this paper (called PPRILBP). To protect image content,… More >

  • Open Access

    ARTICLE

    Multi-Level Fusion in Ultrasound for Cancer Detection Based on Uniform LBP Features

    Diyar Qader Zeebaree1, Adnan Mohsin Abdulazeez2, Dilovan Asaad Zebari3,*, Habibollah Haron4, Haza Nuzly Abdull Hamed4

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3363-3382, 2021, DOI:10.32604/cmc.2021.013314

    Abstract Collective improvement in the acceptable or desirable accuracy level of breast cancer image-related pattern recognition using various schemes remains challenging. Despite the combination of multiple schemes to achieve superior ultrasound image pattern recognition by reducing the speckle noise, an enhanced technique is not achieved. The purpose of this study is to introduce a features-based fusion scheme based on enhancement uniform-Local Binary Pattern (LBP) and filtered noise reduction. To surmount the above limitations and achieve the aim of the study, a new descriptor that enhances the LBP features based on the new threshold has been proposed. This paper proposes a multi-level… More >

  • Open Access

    ARTICLE

    Multi Criteria Decision Making System for Parking System

    Manjur Kolhar*, Abdalla Alameen

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 101-116, 2021, DOI:10.32604/csse.2021.014915

    Abstract System supported smart parking can reduce traffic by making it stress free to locate empty parking spaces, hence lowering the risk of unfocussed driving. In this study, we propose a smart parking system using deep learning and an application-based approach. This system has two modules, one module detects and recognizes a license plate (LP), and the other selects a parking space; both modules use deep learning techniques. We used two modules that work independently to detect and recognize an LP by using an image of the vehicle. To detect parking space, only deep learning techniques were used. The two modules… More >

  • Open Access

    ARTICLE

    The Big Data Analysis on the Camera-based Face Image in Surveillance Cameras*

    Zhiguo Yan, Zheng Xu, Jie Dai

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 123-132, 2018, DOI:10.1080/10798587.2016.1267251

    Abstract In the Big-Data era, currently how to automatically realize acquisition, refining and fast retrieval of the target information in a surveillance video has become an urgent demand in the public security video surveillance field. This paper proposes a new gun-dome camera cooperative system, which solves the above problem partly. The system adopts a master-slave static panorama-variable view dualcamera cooperative video-monitoring system. In this dual-camera system the gun camera static camera) with a wide viewing -angle lenses is in charge of the pedestrian detection and the dome camera can maneuver its focus and cradle orientation to get the clear and enlarged… More >

  • Open Access

    ARTICLE

    Privacy Protection for Medical Images Based on DenseNet and Coverless Steganography

    Yun Tan1, Jiaohua Qin1, *, Hao Tang2, Xuyu Xiang1, Ling Tan2, Neal N. Xiong3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1797-1817, 2020, DOI:10.32604/cmc.2020.010802

    Abstract With the development of the internet of medical things (IoMT), the privacy protection problem has become more and more critical. In this paper, we propose a privacy protection scheme for medical images based on DenseNet and coverless steganography. For a given group of medical images of one patient, DenseNet is used to regroup the images based on feature similarity comparison. Then the mapping indexes can be constructed based on LBP feature and hash generation. After mapping the privacy information with the hash sequences, the corresponding mapped indexes of secret information will be packed together with the medical images group and… More >

  • Open Access

    ARTICLE

    A Face Recognition Algorithm Based on LBP-EHMM

    Tao Li1, Lingyun Wang1, Yin Chen1,*, Yongjun Ren1, Lei Wang1, Jinyue Xia2

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 59-68, 2019, DOI:10.32604/jai.2019.06346

    Abstract In order to solve the problem that real-time face recognition is susceptible to illumination changes, this paper proposes a face recognition method that combines Local Binary Patterns (LBP) and Embedded Hidden Markov Model (EHMM). Face recognition method. The method firstly performs LBP preprocessing on the input face image, then extracts the feature vector, and finally sends the extracted feature observation vector to the EHMM for training or recognition. Experiments on multiple face databases show that the proposed algorithm is robust to illumination and improves recognition rate. More >

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