Farah Diyana Abdul Rahman

An Improved Image Steganography algorithm based on PVD

Zarina Mohd Noh*, Abdul Rahman Ramli, Marsyita Hanafi, M Iqbal Saripan, Ridza Azri Ramlee 1,2,3,4 Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia 1,5 Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 75450 Durian Tunggal, Melaka, Malaysia

Edge Dissimilarity Reduced-Reference Quality Metric with Low Overhead Bitrate

Received Nov 19, 2017 Revised Jan 10, 2018 Accepted Feb 15, 2018 In multimedia transmission, it is important to rely on an objective quality metric which accurately represents the subjective quality of processed images and video sequences. Reduced-reference metrics make use of sideinformation that is transmitted to the receiver for estimating the quality of the received sequence with low complexity. In this paper, an Edge-based Dissimilarity Reduced-Reference video quality metric with low overhead bitrate is proposed. The metric is evaluated by finding the dissimilarity between the edge information of original and distorted sequences. The edge degradation can be detected in this manner as perceived video quality is highly associated with edge structural. Due to the high overhead using the Soergel distance, it is pertinent to find a way to reduce the overhead while maintaining the edge information that can convey the quality measure of the sequences. The effects of different edge detection operator, video resolution and file compressor are investigated. The aim of this paper is to significantly reduce the bitrate required in order to transmit the side information overhead as the reduced reference video quality metric. From the results obtained, the side information extracted using Sobel edge detector maintained consistency throughout the reduction of spatial and temporal down-sample.

Recognition of Metal Objects inside Wall using Antipodal Vivaldi Antenna

Received Dec 04, 2017 Revised Jan 11, 2018 Accepted Apr 15, 2018 Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.A Weblogs contains the history of User Navigation Pattern while user accessing the websites. The user navigation pattern can be analyzed based on the previous user navigation that is stored in weblog. The weblog comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The aim of the research is to identifying the interested user behavior and not interested user behavior based on classification. The process of identifying user interest, it consists of Modified Span Algorithm and Personalization Algorithm based on the classification algorithm user prediction can be analyzed. The research work explores to analyze user prediction behavior based on user personalization that is captured from weblogs.Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.

No-Reference Spatio-temporal Activity Difference PSNR Estimation

Monitoring and maintaining acceptable Quality of Experience for end-users are main purposes for video service providers. Multicast network error transmission can critically degrade the perceived visual quality. This paper presents a novel no-reference video quality estimation using spatial and temporal perceptual activity over multicast IEEE 802.11n. This allows real-time monitoring and detection of visual degradations caused by network error transmission. The spatial and temporal perceptual activity features are extracted from each frame which subjected to network error transmission conditions. These features are implemented in the proposed method to produce video quality estimation and compared against the performance of full-reference objective video quality metrics. The proposed method is shown to be well correlated over a wide range of packet error rates and demonstrates that video quality can be detected by using spatial and temporal perceptual activity features with high accuracy which allows maintaining quality perceived by the end-users.

Link Adaptation Based on Video Quality Monitoring for H.264/AVC Video Transmission over WLANs

Link adaptation algorithms employed by wireless routers traditionally use retransmission to achieve high error-free data throughput. Such methods do not take into account the delay sensitive nature of video data. In this paper, we investigate the use of reduced-reference video quality monitoring for video oriented link adaptation. Estimation of the quality degradation due to channel errors is performed at the receiver side using the No-Reference video quality Monitoring metric. The estimates are sent to the encoder side where, combined with mean squared error values for the encoded video, they form a reduced reference metric that gives information about the quality of the video at the receiver. Link adaptation is then performed using this reduced reference metric.