scholarly journals DIGITAL IMAGE ANALYSIS USING FLATBED SCANNING SYSTEM FOR PURITY TESTING OF RICE SEED AND CONFIRMATION BY GROW OUT TEST

2018 ◽  
Vol 19 (2) ◽  
pp. 49 ◽  
Author(s):  
Mira Landep Widiastuti ◽  
Aris Hairmansis ◽  
Endah Retno Palupi ◽  
Satriyas Ilyas
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Recognition Rate ◽  
Morphological Characteristics ◽  
Scanning System ◽  
Rice Seed ◽  
Red Rice ◽  
Rice Varieties ◽  
Purity Testing

<p class="abstrakinggris">The common method used for purity testing of rice seed is human visual observation. This method, however, has a high degree of subjectivity when dealing with different rice varieties which have similar morphology. Digital image analysis with flatbed scanning for purity testing of rice seed was proposed by investigating the morphology of rice seeds and confirmation by grow out test (GOT) in the field. Two extra-long seed varieties were used in this study including a red rice Aek Sibundong and an aromatic rice Sintanur. The identification on 14 parameters of morphological characteristics indicated that only six parameters were correlated, i.e. area, feret, minimum feret, aspect ratio, round, and solidity. The purity of rice seed can be effectively determined using digital image analysis of spikelet color and shape. Based on the discriminant analysis of the digital image the recognition rate of rice seed purity was higher than 99.2% for shape and 93.55% for color. The method, therefore, has a potential to be used as a complement in rice seed purity testing to increase the accuracy of human visual method and it is more sensitive than GOT.</p>

Polymorphism of oat kernel size and shape in several Canadian oat cultivars

1995 ◽  
Vol 75 (1) ◽  
pp. 105-109 ◽  
Author(s):  
L. N. Pietrzak ◽  
R. G. Fulcher
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Avena Sativa ◽  
Digital Image Analysis ◽  
Diversity Index ◽  
Morphological Characteristics ◽  
Kernel Size ◽  
Seed Shape ◽  
Size And Shape ◽  
Oat Cultivars

This study used digital image analysis to quantify variation of morphological characteristics of oat kernels. Ten Canadian oat varieties grown in 1984 and 1985 at five and four locations, respectively, were examined. Statistically significant differences in polymorphism among varieties collected from the same location were observed. It appeared that the genetic diversity of all analyzed varieties is quite high, and results from a broad range of kernel sizes are evenly distributed within population. The environment has little effect on the polymorphism of seed shape. The same varieties grown in different locations appeared to have almost the same diversity index, and the aspect ratio (AR) depends primarily on the genetic structure of the population. However, the diversity index of AR for each variety calculated over all locations appeared to be almost the same. Key words: Oat, Avena sativa, digital image analysis, size and shape

Digital Image Analysis of the Larynx

2000 ◽  
Vol 10 (2) ◽  
pp. 7-9
Author(s):  
Yaser Natour ◽  
Christine Sapienza ◽  
Mark Schmalz ◽  
Savita Collins
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis

scholarly journals Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis

2019 ◽  
Vol 8 (3) ◽  
pp. 11 ◽  
Author(s):  
Gustav Stålhammar ◽  
Thonnie Rose O. See ◽  
Stephen Phillips ◽  
Stefan Seregard ◽  
Hans E. Grossniklaus
Keyword(s):  
Image Analysis ◽  
Uveal Melanoma ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Melanoma Metastasis

Quantitative evaluation of elderly skin based on digital image analysis

2008 ◽  
Vol 14 (2) ◽  
pp. 192-200 ◽  
Author(s):  
Hiromasa Tanaka ◽  
Gojiro Nakagami ◽  
Hiromi Sanada ◽  
Yunita Sari ◽  
Hiroshi Kobayashi ◽  
...  
Keyword(s):  
Image Analysis ◽  
Quantitative Evaluation ◽  
Digital Image ◽  
Digital Image Analysis

scholarly journals In vitro validation of Digital Image Analysis Sequence (DIAS) for the assessment of the marginal fit of cement-retained implant-supported experimental crowns

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Aristeidis A. Villias ◽  
Stefanos G. Kourtis ◽  
Hercules C. Karkazis ◽  
Gregory L. Polyzois
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Confidence Level ◽  
Digital Image Analysis ◽  
Statistical Tests ◽  
Interobserver Reliability ◽  
Intraclass Correlation ◽  
Marginal Fit ◽  
Smallest Detectable Change ◽  
The Mean

Abstract Background The replica technique with its modifications (negative replica) has been used for the assessment of marginal fit (MF). However, identification of the boundaries between prosthesis, cement, and abutment is challenging. The recently developed Digital Image Analysis Sequence (DIAS) addresses this limitation. Although DIAS is applicable, its reliability has not yet been proven. The purpose of this study was to verify the DIAS as an acceptable method for the quantitative assessment of MF at cemented crowns, by conducting statistical tests of agreement between different examiners. Methods One hundred fifty-one implant-supported experimental crowns were cemented. Equal negative replicas were produced from the assemblies. Each replica was sectioned in six parts, which were photographed under an optical microscope. From the 906 standardized digital photomicrographs (0.65 μm/pixel), 130 were randomly selected for analysis. DIAS included tracing the profile of the crown and the abutment and marking the margin definition points before cementation. Next, the traced and marked outlines were superimposed on each digital image, highlighting the components’ boundaries and enabling MF measurements. One researcher ran the analysis twice and three others once, independently. Five groups of 130 measurements were formed. Intra- and interobserver reliability was evaluated with intraclass correlation coefficient (ICC). Agreement was estimated with the standard error of measurement (SEM), the smallest detectable change at the 95% confidence level (SDC95%), and the Bland and Altman method of limits of agreement (LoA). Results Measured MF ranged between 22.83 and 286.58 pixels. Both the intra- and interobserver reliability were excellent, ICC = 1 at 95% confidence level. The intra- and interobserver SEM and SDC95% were less than 1 and 3 pixels, respectively. The Bland–Altman analysis presented graphically high level of agreement between the mean measurement of the first observer and each of the three other observers’ measurements. Differences between observers were normally distributed. In all three cases, the mean difference was less than 1 pixel and within ± 3 pixels LoA laid at least 95% of differences. T tests of the differences did not reveal any fixed bias (P > .05, not significant). Conclusion The DIAS is an objective and reliable method able to detect and quantify MF at ranges observed in clinical practice.

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