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Sujatha, T.
- Effect of Cooking on the Phytonutrient Content of Selected Edible Flowers
Abstract Views :590 |
PDF Views:404
Authors
Affiliations
1 Department of Nutrition and Dietetics, PSG Arts and Science College, Coimbatore-641014, IN
2 Department of Nutrition and Dietetics, Muslim Arts College, Thiruvithancode, IN
1 Department of Nutrition and Dietetics, PSG Arts and Science College, Coimbatore-641014, IN
2 Department of Nutrition and Dietetics, Muslim Arts College, Thiruvithancode, IN
Source
FoodSci: Indian Journal of Research in Food Science and Nutrition, Vol 2, No 1 (2015), Pagination: 1-4Abstract
Phytonutrients are active compounds in plants that have been shown to provide benefit to humans when consumed. The phytonutrient content of two edible flowers were analyzed. Two matured edible flowers namely banana flower and neem flower were selected and studied. The flowers are seasonally available and are being used as natural food. The present study is involved in finding out the effect of different cooking process on phytonutrient content of the selected edible flowers. Cooking methods play a major role in altering the amount and nature of these phytonutrients. Maximum loss of the phytonutrients occurred in the selected edible flowers due to pressure cooking.Keywords
Cooking Process, Edible Flowers, Phytonutrients.References
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- Lossless Image Compression using Different Encoding Algorithm for Various Medical Images
Abstract Views :120 |
PDF Views:1
Authors
T. Sujatha
1,
K. Selvam
1
Affiliations
1 Department of Computer Applications, Dr. MGR Educational and Research Institute, IN
1 Department of Computer Applications, Dr. MGR Educational and Research Institute, IN
Source
ICTACT Journal on Image and Video Processing, Vol 12, No 4 (2022), Pagination: 2704-2709Abstract
In the medical industry, the amount of data that can be collected and kept is currently increasing. As a result, in order to handle these large amounts of data efficiently, compression methods must be re-examined while taking the algorithm complexity into account. An image processing strategy should be explored to eliminate the duplication image contents, so boosting the capability to retain or transport data in the best possible manner. Image Compression (IC) is a method of compressing images as they are being stored and processed. The information is preserved in a lossless image compression technique which allows for exact image reconstruction from compressed data with retain the quality of image to higher possible extend but it does not significantly decrease the size of the image. In this research work, the encoding algorithm is applied to various medical images such as brain image, dental x-ray image, hand x ray images, breast mammogram images and skin image can be used to minimize the bit size of the image pixels based on the different encoding algorithm such as Huffman, Lempel-Ziv-Welch (LZW) and Run Length Encoding (RLE) for effective compression and decompression without any quality loss to reconstruct the image. The image processing toolbox is used to apply the compression algorithms in MATLAB. To assess the compression efficiency of various medical images using different encoding techniques and performance indicators such as Compression Ratio (CR) and Compression Factor (CF). The LZW technique compresses binary images; however, it fails to generate a lossless image in this implementation. Huffman and RLE algorithms have a lower CR value, which means they compress data more efficiently than LZW, although RLE has a larger CF value than LZW and Huffman. When fewer CR and more CF are recorded, RLE coding becomes more viable. Finally, using state-of-the-art methodologies for the sample medical images, performance measures such as PSNR and MSE is retrieved and assessed.Keywords
Lossless Image Compression, Huffman Coding, Lempel-Ziv-Weich, Run Length EncodingReferences
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- A.C.B. Monteiro, R.P. França and P.D.M. Negrete, “Metaheuristics Applied to Blood Image Analysis”, Lecture Notes in Electrical Engineering, Vol. 696, pp. 117-135, 2021.
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- W.A. Ali, K.N. Manasa and P. Sandhya, “A Review of Current Machine Learning Approaches for Anomaly Detection in Network Traffic”, Journal of Telecommunications and the Digital Economy, Vol. 8, No. 1, pp. 64-95, 2020.
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- Med Karim Abdmouleh, Atef Masmoudi and Med Salim Bouhlel. “A New Method which Combines Arithmetic Coding with RLE for Lossless Image Compression”, Scientific Research Publishing, Vol. 2021, pp. 1-7, 2021.
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- Med Karim Abdmouleh, Atef Masmoudi and Med Salim Bouhlel, “A New Method which Combines Arithmetic Coding with RLE for Lossless Image Compression”, Scientific Research Publishing, Vol. 2021, pp. 1-12, 2021.
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