Zaidi Razak

Passive video forgery detection techniques: A survey

Technological advancement of various video and image processing tools has made tempering of digital video easy and faster. This review paper focuses on passive techniques that are employed for detecting forgeries in a digital video. Passive forgery detection techniques are methods used for detecting the authenticity of a video without depending on pre-embedded information. The techniques exploit the use of statistical or mathematical properties that are distorted as a result of video tempering for forgery detection. Passive video forgery detection approach has a great prospect in multimedia security, information security and pattern recognition. In this paper, we divide passive techniques for video forensics into three categories; Statistical correlation of video features, frame-based for detecting statistical anomalies, and the inconsistency features of different digital equipment. The discussion also covers the trends, limitations and idea for improvements of passive forgery detection techniques.

BRAIN-F: Beacon Rate Adaption Based on Fuzzy Logic in Vehicular Ad Hoc Network

Beacon rate adaption is a way to cope with congestion of the wireless link and it consequently decreases the beacon drop rate and the inaccuracy of information of each vehicle in the network. In a vehicular environment, the beacon rate adjustment is strongly dependent on the traffic condition. Due to this, we firstly propose a new model to detect traffic density based on the vehicle’s own status and the surrounding vehicle’s status. We also develop a model based on fuzzy logic namely the BRAIN-F, to adjust the frequency of beaconing. This model depends on three parameters including traffic density, vehicle status and location status. Channel congestion and information accuracy are considered the main criteria to evaluate the performance of BRAIN-F under both LOS and NLOS. Simulation results demonstrate that the BRAIN-F not only reduces the congestion of the wireless link but it also increases the information accuracy.

Jawi Character Speech-to-Text Engine Using Linear Predictive and Neural Network for Effective Reading

Jawi is an old version of Malay Language Writing that need to be preserved. Therefore, it is important to develop tools for teaching kids about Jawi characters and Speech-To-Text (STT) application can serve this purpose well. Unlike English, Jawi uses special characters similar to Arabic Characters. However, its pronunciations are in Malay Language. This uniqueness makes STT development a challenging task. In this paper, we investigate the applicability of Linear Predictive Coding to extract important features from voice signal and Neural Network with Backpropagation to classify and recognize spoken words into Jawi Characters. A total of 225 samples of words in Jawi Characters are recorded from speakers with over 95% accuracy. Jawi Characters Speech-To-Text Engine aims to help students to read Jawi document accurately and independently without the need for close monitoring from parents or teachers.

An authoring toolkit design for educational game content

A new way of teaching using multimedia presentations or game-based technologies are urgently needed in order to engage and sustain students’ learning interests in their learning materials. To achieve that, teachers should be able to produce interactive multimedia learning materials (e.g. educational games) themselves. However, current authoring tools such as Adobe Flash and Macromedia Director are too complex to use by teachers with no computing backgrounds. We would like to address this issue by proposing a simple to use authoring toolkit that will enable teachers to create their own educational game contents. The proposed toolkit operates by using games templates i.e. akin to producing presentation slides using Microsoft Power Point. In this paper, we present the framework in designing such toolkit. Based on this framework, an authoring tool will be developed to enable teachers in Malaysia to author educational game content for teaching basic Jawi words for the primary school children.

High-Speed Shortest Path Co-processor Design

Shortest path algorithms are significant in graph theory and have been applied in many applications such as transportation and networking. Most of the shortest path calculation is performed on general purpose processor where instructions must be run to read the input, compute the result, and set the output which later on will slow down the overall performance. Therefore, the authors proposed a hardware approach which implements FPGA technology to find the shortest path between two nodes. The FPGA approach will demonstrate how parallelism can be used to significantly reduce calculation steps compared to sequential effort. In this paper, A-Star algorithm has been chosen for the shortest path calculation since it can achieve superior time running based on its heuristic behavior.

VHDL implementation of JAWI character recognition via chain code algorithm

The purpose of this paper is to describe a hardware model that can recognize Jawi handwriting manuscript via chain code technique. The model is divided into three modules: character segmentation, image processing (image enhancement, noise reduction, character recognition) and character id searching (via chain code). In the next stage, this model will be implemented using VHSIC hardware description language (VHDL).

A Review on Feature Extraction & Classification Techniques for Biosignal Processing (Part V: Gait Signal)

This paper concentrates on Gait signal processing with the emphasis on Parkinsons’s Disease diagnosis. Gait is a novel biometric intended to recognize human from their walking pattern. This paper discussed in general about feature extraction and classification for Gait application. Among the factor discussed and analysed include the techniques advantages, performance and drawbacks.

Review of hardware implementation of Speech-To-Text Engine for Jawi Character

Jawi is a Malay writing script based on the Arabic script which adds six extra characters to accommodate Malay vocal sounds. Real-Time Speech-To-Text Engine for Jawi Character aims to help students to read Jawi more effectively. In this paper, we investigate the suitable method and device that best for speech-to-text hardware implementation. A complete set of Jawi Speech-To-Text tools will be implements by integrating the hardware with a microphone and Jawi word processor. The speech recognition will use Linear Predictive Coding (LPC) as feature extraction and Neural Network (NN) with Backpropagation will be use as a pattern classification. The implementation of this system will be tested using Xilinx Field Programmable Gate Array (FPGA) board.

Parallel Matrix Multiplication Design for Monocular SLAM

As software profiling is conducted to determine which section of program demand high processing computation in monocular SLAM inverse depth estimation, matrix multiplication is identified to be one of the most time consuming process. The processing is more demanding when the number of features inserted to the image is increased. For that reason, this paper proposes a parallel matrix multiplier design which could accelerate the execution time. In this design, Field Programmable Gate Array (FPGA) technology which allows parallel design to be implemented is presented. The design manipulates existing classical matrix multiplication algorithm into an architecture that would enable data to be processed concurrently.

The Design of Discrete Wavelet Transformation Chip

In this paper, an explanation on the need for a special discrete wavelet transformation hardware is presented. The development processes that have been carried out which includes simulation (both in MATLAB? and SYNOPSYS?) and synthesis which also used SYNOPSYS? tools is described together with a discussion on specific design issues in the coordination of the entities.