A busy lifestyle led people to buy readymade clothes from retail stores with or without fit-on, expecting a perfect match. The existing online cloth shopping systems are capable of providing only 2D images of the clothes, which does not lead to a perfect match for the individual user. To overcome this problem, the apparel industry conducts many studies to reduce the time gap between cloth selection and final purchase by introducing “virtual dressing rooms.” This paper discusses the design and implementation of augmented reality “virtual dressing room” for real-time simulation of 3D clothes. The system is developed using a single Microsoft Kinect V2 sensor as the depth sensor, to obtain user body parameter measurements, including 3D measurements such as the circumferences of chest, waist, hip, thigh, and knee to develop a unique model for each user. The size category of the clothes is chosen based on the measurements of each customer. The Unity3D game engine was incorporated for overlaying 3D clothes virtually on the user in real time. The system is also equipped with gender identification and gesture controllers to select the cloth. The developed application successfully augmented the selected dress model with physics motions according to the physical movements made by the user, which provides a realistic fitting experience. The performance evaluation reveals that a single depth sensor can be applied in the real-time simulation of 3D cloth with less than 10% of the average measurement error.

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Diabetic retinopathy, that affects the blood vessels of the retina, is considered to be the most serious complication prevalent among diabetic patients. If detect successfully at an early stage, ophthalmologist would be able to treat the patients by advanced laser treatment to prevent total blindness. In this paper, we propose a technique based on morphological image processing and fuzzy logic to detect hard exudates from diabetic retinopathy retinal images. At the initial stage, the exudates are identified using mathematical morphology that includes elimination of the optic disc. Subsequently, hard exudates are extracted using an adaptive fuzzy logic algorithm that uses values in the RGB colour space of retinal image to form fuzzy sets and membership functions. The fuzzy output for all the pixels in every exudate is calculated for a given input set corresponding to red, green and blue channels of a pixel in an exudate. This fuzzy output is computed for hard exudates according to the proportion of the area of the hard exudates. By comparing the results with hand-drawn ground truths, we obtained sensitivity and specificity of detecting hard exudates as 75.43% and 99.99%, respectively.

Extracting the actual boundary of a tooth is useful in order to obtain an accurate shape to design a false tooth. A tooth in a dental X-ray image, however, exhibits sharp corners at its root making the boundary extraction task difficult. In this paper, a new technique based on active contours is presented along with a novel modification to detect sharp corners of objects of interest. The proposed technique has the ability to incorporate prior knowledge of significant corners of teeth into the deforming contour and is able to deform towards the boundaries of the object without surpassing corner points. Experimental results with several synthetic and real medical images show the ability of the new technique to extract features of interest from images consisting of sharp corners with increased accuracy.

Applications that involve monitoring of water quality parameters require measuring devices to be placed at different geographical locations but are controlled centrally at a remote site. The measuring devices in such applications need to be small, consume low power, and must be capable of local processing tasks facilitating the mobility to span the measuring area in a vast geographic area. This paper presents the design of a generalized, low-cost, reconfigurable, reprogrammable smart sensor node using a ZigBee with a Field-Programmable Gate Array (FPGA) that embeds all processing and communication functionalities based on the IEEE 1451 family of standards. Design of the sensor nodes includes processing and transducer control functionalities in a single core increasing the speedup of processing power due to interprocess communication taking place within the chip itself. Results obtained by measuring the pH value and temperature of water samples verify the performance of the proposed sensor node.