Abstrac. A fast method presented within this paper to find transparent liquid viscosity. An introduced tracking algorithm in image processing used to find a terminal velocity automatically of a falling ball in a tube that filled with a tested liquid. Terminal velocity considered an important parameter to find a liquid viscosity. Therefore, four iron balls, with different diameters and a smartphone camera are used to measure the falling ball terminal velocity. The estimated velocity from the introduced algorithm is compared with the calculated velocity and shows a good matching. The second algorithm used to estimate the viscosity of the tested liquid. The limitation of the ball diameter around 5mm to measure the terminal velocity. The result shows error matching between the fitting data and the estimated data ranging (0.00-0.1%). This method is a faster and easier experiment to use to find any transparent liquid viscosity comparing with a viscometer.
A challenge of adding a new feature to the optical properties of a camera is solved in this paper. Image processing gives the possibility to enhance the quality, resolution and details of images fast these days. Within this paper, the introduced algorithm used to determine the vision angles (horizontal and vertical) of a digital camera (Nikon). The quality and efficiency of the camera are evaluated using determine the spatial resolution of the captured images. A scale factor algorithm is used also in this paper. A mathematical model introduced to describe the camera angle vision. This model works with different zoom degrees and different camera-object distances. Thus, a general mathematical equation obtained which describes the real image. The comparisons between the real and resulted images give a strong matching with small error rate.
Human looking forward to living in a modern and comfortable environment like smart houses. In this study, an effective user-friendly smart home prototype designed with low cost. The prototype contains eight of Light Emitting Diode (LED) considered as home appliances and controlled in real-time using eight suggested hand cases. The hand cases have different position regarded to head and shoulder levels. The hand position is detected using a new suggested algorithm programmed in Matlab software. Viola-Jones method used to detect hand in a complex background (hand with a different background) by training computer using positive (hand) and negative (non-hand) image datasets. To make computer training faster and accurate, a new idea depends on a skin detection used before computer training to determine the location and size of all positive images automatically. The LEDs in prototype switched ON/OFF using the suggested hand cases in a fast time. Where the response time of LEDs to hand cases was 0.43 second.
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