Papers by Mohd Hafizuddin Mohd Yusof
DEMO VIDEO - ICCASA2013 - HumanSensing Tabletop Final
A video demonstrating the tracking system in action with 5 simultaneous users working on the table.
Proceedings. Student Conference on Research and Development, 2003. SCORED 2003., 2003
l i z u~l d i i i . v u s o l i i r ! n a n u . i~~~, madasii(crlitcc.tiq.~~iii.~ii Abstruct-This... more l i z u~l d i i i . v u s o l i i r ! n a n u . i~~~, madasii(crlitcc.tiq.~~iii.~ii Abstruct-This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature images are binarized and resized to a fixed size window and are then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning' approach. The features of consideration are normalized vector angle (a) and distance (y) from each box. Each feature extracted from sample signatures gives rise to fuzzy sets. Since the choice of a proper fuzzification hnction is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in hzzy sets. This function is employed to develop a complete forgery detection and verification system,
Fuzzy Modeling Based Recognition of Multi-font Numerals
Lecture Notes in Computer Science, 2003
In this paper, we present a new scheme for off-line recognition of multi-font numerals using the ... more In this paper, we present a new scheme for off-line recognition of multi-font numerals using the Takagi-Sugeno (TS) model. In this scheme, the binary image of a character is partitioned into a fixed number of sub-images called boxes. The features consist of normalized vector ...
Pattern Recognition, 2005
Automatic signature verification is a well-established and an active area of research with numero... more Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance.
Emotion Recognition in Speech Using Fuzzy Approach
This paper uses LPC analysis to extract emotion features from speech. From this analysis, 18 feat... more This paper uses LPC analysis to extract emotion features from speech. From this analysis, 18 features namely pitch, jitter, energy, duration and 14 LPC coefficients are extracted from each voice sample to represent the emotion features of six basic emotions; happiness, sadness, fear, anger, surprise and disgust. These 18 features extracted from different samples give rise to 18 fuzzy sets.
Signal Processing and …, 2003
Absrmcl-This paper discusses an approach towards automatic recognition of emotion in speech using... more Absrmcl-This paper discusses an approach towards automatic recognition of emotion in speech using computer. First, a design for the emotion recognizer is proposed. LP analysis algorithm has been used far the speech emotion parameter extraction. A total of 22 speech features have been selected to represent each emotion. A database consisting of emotional Malay and English voice samples has been developed far training and recognition purposes. Fuzzy concept has been applied to recognize emotion of the selected voice sample. The result from computer recognition is compared to the human recognition rate to confirm the reliability of the result and also to explore how well people and computer can recognize emotion in speech. It is found that computer recognition of emotion is possible and the average recognition rate of 66% is satisfactory based on the comparison from the human perception. According to the confusion matrix table for both human and computer recognition, it is shown that the way human interprets emotion is different from computer.
The Second National …, 2010
Biennial Australian Pattern …, 2003
An innovative approach for extracting signatures from bank cheque images and other documents is p... more An innovative approach for extracting signatures from bank cheque images and other documents is proposed based on the integration of the crop method with the sliding window technique. The idea is to estimate the approximate area in which the signature lies using the sliding window technique. In this approach, a window of adaptable height and width is moved over the image; one pixel at a time and the density of pixels within the window is calculated. This density is then used to find the entropy, which in turn helps fit the box that can segment the signature. The signatures thus extracted are then fed to a known fuzzy based off-line signature verification and forgery detection system. The proposed method has been applied with almost 100% success on several bank cheques from India, Malaysia and Australia. Signature extraction has also been shown on two typical types of documents which have varied and noisy backgrounds.
Tabletop displays are gaining interests in gaming environments. Computer Game in the genre of boa... more Tabletop displays are gaining interests in gaming environments. Computer Game in the genre of board games, competitive actions, real-time strategies are amongst those that are suitable for tabletop displays. Currently most games developed for tabletops use physical objects with markings as the controllers and standard touch and gestures as the inputs. To extend the present limits of gestures and touch, we present an implementation of high performance sensor-based input modality as an extension to tabletop displays. The additional input modality has the capability to sense and track users" bodies while they are interacting with the table. This paper outlines the configuration of the sensors, the tracking accuracy test result and informal evaluations of the system. We emphasise the simplicity of sensor configuration, cost, robustness and high performance in the design of tabletop sensor systems. To demonstrate the capability of our system, we developed a computer game "Body Pong" where each player controls a paddle assigned automatically to him/her by moving his/her position left and right. The game demonstrates how context-awareness adapts when number of users changes during game play.
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Papers by Mohd Hafizuddin Mohd Yusof