A procedure was developed to predict moisture loss from cooling data of potato packed in gunny bags and stacked on wooden platforms in commercial cold stores. To predict the moisture loss, mass transfer coefficients k c and k m were estimated during the storage period, which were found to decrease with time. The calculated time average k c and k m values were 1.83 ¥ 10 -4 m/s and 2.31 ¥ 10 -10 kg/s·m 2 ·Pa during the transient cooling period and 1.59 ¥ 10 -4 m/s and 2.27 ¥ 10 -10 kg/s·m 2 ·Pa for the rest of the storage period, respectively. The estimated moisture losses were 4.8, 4.74 and 4.78%, at the center of three different stacks, for a storage period of 8 months. The corresponding experimentally measured weight losses at the center of the same stacks were 5.2, 5.1 and 5.26% with a variation of 11, 7.5 and 10.2%, respectively. Therefore, the procedure adopted in this study may be used to assess the moisture loss from potatoes under the different storage conditions. The effect of relative humidity (RH) and potato temperature on moisture loss was also predicted using the developed procedure. Decrease in RH of the storage air increased the moisture loss. The potatoes stored below 85% RH incurred more than 7% water loss. Therefore, 88-90% RH in the cold store may be used to limit the maximum moisture loss within the permissible limit of 5% even after 8 months of storage. It was also found that increasing the potato temperature exponentially increased the rate of moisture loss. 3 Corresponding Journal of Food Process Engineering 28 (2005) 397-416. All Rights Reserved. © Copyright 2005, Blackwell Publishing 397 398 M.K. CHOURASIA ET AL.

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Motion Estimation involves the most computation as compared to other processes in the entire video compression process. The challenge is to reduce the computation cost and computation time to calculate motion vector compared to Full Search algorithm for motion vector estimation. In this paper, it is proposed to implement an algorithm which will find finer estimation of motion for higher motion zone and take less time in computing motion vector for less movement zone.

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With the growth of globalisation, security has been a major concern in digital exchange of medical information. Data hiding, also referred as watermarking, was introduced to authenticate medical data which is sent over the network. Watermarking of electronic patient reports (EPR) for telemedicine demands robust, imperceptible, high payload techniques. Blood vessel extraction is mainly used for diabetic retinopathy (DR) for automatic extraction and classification of severity of diseases. In our current work, blood vessel from fundus images is extracted using K-means segmentation. Afterwards, EPR is hidden using interpolation and trigonometric functions in fundus image. Finally, blood vessel is extracted from the watermarked image to measure the changes in accuracy of the proposed system. The percentage difference (< 0.25%) of accuracy in fundus images before watermarking and after watermarking claims the retention of devalorisation of vessel extraction accuracy measurement. High peak signal to noise ratio (PSNR) value (> 36) and high correlation (> 87%) between original and watermarked retinal image, establishes the robustness of the proposed non-blind watermarking method.Keywords: blood vessel extraction; non-blind watermarking; electronic patient report; EPR; K-means; peak signal to noise ratio; PSNR. Effect of trigonometric functions-based watermarking on blood vessel extraction 91Reference to this paper should be made as follows: Dey, N., Ahmed, S.S., Chakraborty, S., Maji, P., Das, A. and Chaudhuri, S.S. (2017) 'Effect of trigonometric functions-based watermarking on blood vessel extraction: an application in ophthalmology imaging', Int.