scholarly journals Image Texture Analysis and Gas Sensor Array Studies Applied to Vanilla Encapsulation by Octenyl Succinic Anhydride Starches

2013 ◽  
Vol 2 (2) ◽  
pp. 36 ◽  
Author(s):  
Silvio D. Rodríguez ◽  
Tom F. Wilderjans ◽  
Natalia Sosa ◽  
Delia L. Bernik
Keyword(s):  
Texture Analysis ◽  
Gas Sensor ◽  
Succinic Anhydride ◽  
Sensor Array ◽  
Image Texture ◽  
Joint Analysis ◽  
Image Texture Analysis ◽  
Gas Sensor Array ◽  
Octenyl Succinic Anhydride ◽  
Occurrence Matrix

Native starch derivatization with octenyl succinic anhydride (OSA) is a chemical modification designed to enhance flavor microencapsulation performance. Hi Cap 100 and Capsul are two OSA starches derived from waxy maize base, which are especially suited for encapsulation processes. This work performs for the first time the encapsulation of vanilla extract with Capsul and Hi Cap 100 using both spray and freeze drying procedures. The encapsulation efficiency was studied correlating the starch texture with the aroma retention. Texture analysis was accomplished by means of grey level co-occurrence matrix feature extraction (GLCM), yielding image parameters that clearly differ in function of the type of starch and the drying method used for the encapsulation of the flavor. In parallel, the data recorded with a gas sensor array (e-nose) and analyzed by unsupervised multivariate methods allowed to follow up the evolution of the aroma through the whole process. The joint analysis of the GLCM and sensor array recorded data indicates that Capsul shows a higher capacity for vanilla encapsulation than Hi Cap 100. In addition, the obtained converging information from GLCM and e-nose data clearly indicates that particle texture and aroma encapsulation are connected.

Improving the Distinction between Benign and Malignant Breast Lesions: The Value of Sonographic Texture Analysis

1993 ◽  
Vol 15 (4) ◽  
pp. 267-285 ◽  
Author(s):  
Brian S. Garra ◽  
Brian H. Krasner ◽  
Steven C. Horii ◽  
Susan Ascher ◽  
Seong K. Mun ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Benign Lesion ◽  
Ultrasound Image ◽  
Image Texture ◽  
Breast Lesions ◽  
Image Texture Analysis ◽  
True Nature ◽  
Malignant Breast ◽  
Occurrence Matrix ◽  
Ultrasound Scanner

To improve the ability of ultrasound to distinguish benign from malignant breast lesions, we used quantitative analysis of ultrasound image texture. Eight cancers, 22 cysts, 28 fibroadenomata, and 22 fibrocystic nodules were studied. The true nature of each lesion was determined by aspiration (for some cysts) or by open biopsy. Analysis of image texture was performed on digitized video output from the ultrasound scanner using fractal analysis and statistical texture analysis methods. The most useful features were those derived from co-occurrence matrices of the images. Using two features together (contrast of a co-occurrence matrix taken in an oblique direction, and correlation of a co-occurrence matrix taken in the horizontal direction), it was possible to exclude 78% of fibroadenomata, 73% of cysts, and 91% of fibrocystic nodules while maintaining 100% sensitivity for cancer. These findings suggest that ultrasonic image texture analysis is a simple way to markedly reduce the number of benign lesion biopsies without missing additional cancers.

scholarly journals The Effect of Rider:Horse Bodyweight Ratio on the Superficial Body Temperature of Horse’s Thoracolumbar Region Evaluated by Advanced Thermal Image Processing

Animals ◽  
2022 ◽  
Vol 12 (2) ◽  
pp. 195
Author(s):  
Małgorzata Domino ◽  
Marta Borowska ◽  
Anna Trojakowska ◽  
Natalia Kozłowska ◽  
Łukasz Zdrojkowski ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Texture Features ◽  
Image Texture ◽  
Gray Level ◽  
Image Texture Analysis ◽  
Thermal Images ◽  
Thoracolumbar Region ◽  
Thermal Features ◽  
Occurrence Matrix ◽  
The Impact

Appropriate matching of rider–horse sizes is becoming an increasingly important issue of riding horses’ care, as the human population becomes heavier. Recently, infrared thermography (IRT) was considered to be effective in differing the effect of 10.6% and 21.3% of the rider:horse bodyweight ratio, but not 10.1% and 15.3%. As IRT images contain many pixels reflecting the complexity of the body’s surface, the pixel relations were assessed by image texture analysis using histogram statistics (HS), gray-level run-length matrix (GLRLM), and gray level co-occurrence matrix (GLCM) approaches. The study aimed to determine differences in texture features of thermal images under the impact of 10–12%, >12 ≤15%, >15 <18% rider:horse bodyweight ratios, respectively. Twelve horses were ridden by each of six riders assigned to light (L), moderate (M), and heavy (H) groups. Thermal images were taken pre- and post-standard exercise and underwent conventional and texture analysis. Texture analysis required image decomposition into red, green, and blue components. Among 372 returned features, 95 HS features, 48 GLRLM features, and 96 GLCH features differed dependent on exercise; whereas 29 HS features, 16 GLRLM features, and 30 GLCH features differed dependent on bodyweight ratio. Contrary to conventional thermal features, the texture heterogeneity measures, InvDefMom, SumEntrp, Entropy, DifVarnc, and DifEntrp, expressed consistent measurable differences when the red component was considered.

Texture Analysis of Turned Surface Images Using Grey Level Co-Occurrence Technique

2011 ◽  
Vol 365 ◽  
pp. 38-43 ◽  
Author(s):  
Anurup Datta ◽  
Samik Dutta ◽  
Surjya K. Pal ◽  
Ranjan Sen ◽  
Sudipta Mukhopadhyay
Keyword(s):  
Surface Roughness ◽  
Texture Analysis ◽  
Image Texture ◽  
Analysis Method ◽  
Grey Level ◽  
Machined Surface ◽  
Image Texture Analysis ◽  
Pixel Pair ◽  
Occurrence Matrix

The main purpose of this work was to study the applicability of an image texture analysis method, namely, the grey level co-occurrence matrix (GLCM) method for the examination of the smoothness of the images of a turned surface. The effect of the variation of the pixel pair spacing (pps) on the construction of the GLCM was also considered and then, contrast and homogeneity were calculated from the GLCMs which served as texture descriptors for the quality of the machined surface. Finally, the variation of these texture descriptors with cutting time was analyzed and compared with the variation of tool wear and surface roughness with cutting time.

Image Texture Analysis based on Color Level Methods using Neural Network

2020 ELEKTRO ◽  
2020 ◽  
Author(s):  
Miroslav Benco ◽  
Patrik Kamencay ◽  
Robert Hudec ◽  
Martina Radilova ◽  
Peter Sykora
Keyword(s):  
Neural Network ◽  
Texture Analysis ◽  
Image Texture ◽  
Image Texture Analysis

Characterization of micrographs and fractographs of Cu-strengthened HSLA steel using image texture analysis

Measurement ◽  
2014 ◽  
Vol 47 ◽  
pp. 130-144 ◽  
Author(s):  
Samik Dutta ◽  
Kaustav Barat ◽  
Arpan Das ◽  
Swapan Kumar Das ◽  
A.K. Shukla ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Hsla Steel ◽  
Image Texture ◽  
Image Texture Analysis

scholarly journals NIMG-21. IMPACT OF GENETIC ALTERATIONS ON TUMOR LOCATIONS AND LESION HETEROGENEITY FOR WHO GRADE 2 AND 3 GLIOMAS: A VOXEL-BASED LESION MAPPING AND IMAGE TEXTURE ANALYSIS OF 201 GLIOMAS

2016 ◽  
Vol 18 (suppl_6) ◽  
pp. vi128-vi128
Author(s):  
Manabu Kinoshita ◽  
Hideyuki Arita ◽  
Toshiki Yoshimine ◽  
Masamichi Takahashi ◽  
Yoshitaka Narita ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Genetic Alterations ◽  
Image Texture ◽  
Who Grade ◽  
Image Texture Analysis ◽  
Lesion Mapping

scholarly journals LOCATING GAS SOURCES USING A GAS SENSOR ARRAY

1991 ◽  
Vol 7 (Supple) ◽  
pp. 1565-1568 ◽  
Author(s):  
Yukio Hiranaka ◽  
Hiro Yamasaki
Keyword(s):  
Gas Sensor ◽  
Sensor Array ◽  
Gas Sensor Array

Identification and detection of bioactive compounds in turmeric (Curcuma longa L.) using gas sensor array based on molecularly imprinted polymer quartz crystal microbalance

2021 ◽  
Author(s):  
Fajar IAIN Hardoyono ◽  
Kikin Windhani
Keyword(s):  
Gas Sensor ◽  
Bioactive Compounds ◽  
Quartz Crystal Microbalance ◽  
Molecularly Imprinted Polymer ◽  
Quartz Crystal ◽  
Sensor Array ◽  
Curcuma Longa ◽  
Imprinted Polymer ◽  
Molecularly Imprinted ◽  
Gas Sensor Array

This study aimed to identify four bioactive compounds in turmeric (Curcuma longa L.) using gas sensor array based on molecularly imprinted polymer-quartz crystal microbalance (MIP-QCM). Four QCM sensors coated with...

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