Raja Abdullah Raja Ahmad
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Raja Abdullah Raja Ahmad
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Raja Abdullah, Raja Ahmad
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Dct image compression implemented on raspberry pi to compress image captured by cmos image sensor

2021-01-01 , Mohsin I.S. , Muhammad Imran Ahmad , Salman S.M. , Al-Dabagh M.Z.N. , Isa M.N.M. , Raja Abdullah Raja Ahmad

The purpose of compression is to reduce the amount of data at the same time maintain the quality of image and signal for the other purpose. Discrete Cosine Transform (DCT) is a family of image compression where the raw image is transformed to the other domain to produce smaller size of data. DCT transform has low computational complexity and fast processing algorithm. In this project, DCT transform will be implemented using PI camera and Raspberry Pi SBC development board running on an ARM based processor. The raspberry Pi board has an advantage of image processing implementation due to the existing software development tool offered a rich feature for image processing such as OPENCV. The result of applying DCT compression algorithm on images with six compression rate level which are 10, 20, 50, 100, 170 and 200. The best performance can be achieved with compression rate level 200. However, on reducing the quality level of compression rate, the error measurements start becoming worse until a point is reached, where the perceptual difference from the original image can be easily noted.

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Publication

Face recognition system using DCT features implemented on DSP processor

2015 , Raja Abdullah Raja Ahmad

Face recognition is a challenge because the faces always change due to facial expression, direction, light, and scale. Furthermore, it needs good computing techniques for recognition in order to reduce the system’s complexity. Our approach focuses on the local feature extraction in the frequency domain. DCT was proposed as the feature extraction algorithm for face recognition, which captures the important features in the face image and at the same time reduces the feature space. PCA then performs the feature reduction of the extracted image and produces a small size of feature vector. The propose method can reduce data dimension in feature space. The classification is done by using the Euclidean distance between the projection test and projection train images. The algorithm is tested using DSP processor and achieve a same performance with PC based. The extensive experimentations that have been carried out upon standard face databases such as ORL shows that significant performance is achieved by this method, which is 98.5% for best selected test image and 95% for the worst selected test image. Besides that, execution time is also measured, whereby to recognize 40 people, the system only requires 0.3313 second. The proposed method not only offers computational savings, but is also fast and has a high degree of recognition accuracy.

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Smart Management Waiting System for Outpatient Clinic

2023-02-01 , Mohd Wafi Nasrudin , Zainuddin N.S.A. , Raja Abdullah Raja Ahmad , Rashidah Che Yob , Mohd Zamri Zahir Ahmad , Wan Azani Wan Mustafa , Vijayasarveswari Veeraperumal , Zulkifli N.D.M.

Queuing has become a common occurrence in malls, train stations, and others. Queuing especially in healthcare intuitions has become a center of attraction because of the long waiting time either at the registration or in receiving treatments. Therefore, in solving this problem, a smart management waiting system for outpatient clinics is developed by using AppGyver and Backendless as the data storage. This system will be operating by QR code scanning for administrators to obtain patients’ personal information before patients obtain the queue number via MyQUEUE mobile application (patients’ interface). By providing queue numbers through the mobile application, patients don’t have to wait in a small uncomfortable waiting lounge instead patients can wait at their desired places such as cafeteria, in their car, and others. Patients also don’t have to worry about missing their turns because there will be a 10 minutes reminder before their turn. Other than that, there is a feature that digitalized the appointment details which means patients don’t have to worry about missing their appointment book or card. The performance of both systems which are the patients’ interface and administrators’ interface is successfully designed and the output obtained. The administrator is able to assign queue numbers, notify patients 10 minutes before consultation time, and assign follow-up appointments to patients.

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