Engineering characterization of kinnow and tomato for grading using image processing
| dc.contributor.author | Sandhya | |
| dc.contributor.editor | Mahesh Kumar | |
| dc.date.accessioned | 2018-01-12T07:50:42Z | |
| dc.date.available | 2018-01-12T07:50:42Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | The present study was undertaken for characterization of kinnow and tomato based on engineering parameters using digital image processing. The images of kinnow and tomato of different grades were acquired using a digital camera. An algorithm using MATLAB was developed to quantify and process these digital images. The geometric parameters such as axial dimensions, mass, volume, density, sphericity, aspect ratio and ellipsoid ratio were recorded. The size of kinnow varied between 62.50-87.41 mm while tomato had size varying from 30.00-77.62 mm. Results of image analysis showed variation of major axis length from 1597.21 pixels to 1987.1 pixels for kinnow. The bulk density was found to be maximum (0.40 g/cc) for kinnow having size 72-74mm whereas it was highest (0.26 g/cc) for tomato of size 57-66mm. The sphericity varied in the range of 0.92-0.94 for kinnow while tomatoes of variety Punjab Chhuhara were found to be oblong. The results obtained by digital image analysis were compared and verified with the experimental observation recorded by vernier caliper. The volume computed from the images of longitudinal view and lateral view of kinnow and tomato of all the grades showed good correlation with the true volume measured by water displacement method. The Bland-Altman approach was used to plot the agreement between the values measured by both the methods and differences between two methods were normally distributed and were estimated to lie between M - 1.96SD and M + 1.96SD, known as 95% limits of agreement. The paired samples t-test results showed that parameters determined with image processing method was not significantly (P>0.05) different from the same parameters measured with vernier caliper. A linear relationship between mass of the kinnow and tomato and the projected area, volume and axial dimensions was also developed for prediction of mass using image processing. | en_US |
| dc.identifier.uri | http://krishikosh.egranth.ac.in/handle/1/5810039272 | |
| dc.keywords | Geometric parameters, Grades, Image processing, Kinnow, Tomato, Shape parameters | en_US |
| dc.language.iso | en | en_US |
| dc.pages | 134 | en_US |
| dc.publisher | Punjab Agricultural University, Ludhiana | en_US |
| dc.sub | Processing and Food Engineering | en_US |
| dc.subject | null | en_US |
| dc.these.type | M.Tech | |
| dc.title | Engineering characterization of kinnow and tomato for grading using image processing | en_US |
| dc.type | Thesis | en_US |