Non-destructive testing of textured foods by machine vision

Beriat, Pelin
In this thesis, two different approaches are used to extract the relevant features for classifying the aflatoxin contaminated and uncontaminated scaled chili pepper samples: Statistical approach and Local Discriminant Bases (LDB) approach. In the statistical approach, First Order Statistical (FOS) features and Gray Level Cooccurrence Matrix (GLCM) features are extracted. In the LDB approach, the original LDB algorithm is modified to perform 2D searches to extract the most discriminative features from the hyperspectral images by removing irrelevant features and/or combining the features that do not provide sufficient discriminative information on their own. The classification is performed by using Linear Discriminant Analysis (LDA) classifier. Hyperspectral images of scaled chili peppers purchased from various locations in Turkey are used in this study. Correct classification accuracy about 80% is obtained by using the extracted features.


Optimising clarification of carrot juice by bacterial crude pectinase
Uzuner, Sibel; Çekmecelioğlu, Deniz (2015-12-01)
This study was undertaken to search for potential use of crude bacterial pectinase enzyme produced from Bacillus subtilis grown on hazelnut shell hydrolysate in clarification of carrot juice and to optimize the enzyme load, pH and time using the Box-Behnken response surface methodology (RSM). The carrot juice was treated with the crude pectinase enzyme (5.60 U mL(-1)) at different concentrations (0.1-0.5%), pH (4-7), and time (2-6 h). The obtained enzyme was also compared with commercial fungal pectinase at...
Rapid LC and LC/MS for routine analysis of mycotoxins in foods
Senyuva, H.; Gilbert, J.; Özcan Kabasakal, Süreyya; Gurel, N. (Wageningen Academic Publishers, 2008-08-01)
Affinity column clean-up of food samples for mycotoxin analysis produces extracts which are free of co-extractives and therefore require little chromatography for separation and quantification of the target analytes. Using such clean extracts, we report rapid chromatographic methods for aflatoxins B(1), B(2), G(1) and G(2), aflatoxin M(1), ochratoxin A, zearalenone and fumonisins. Using short columns with small particle size packing, HPLC conditions have been developed reducing analysis time typically by 75...
Predicting the effect of hydrophobicity surface on binding affinity of PCP-like compounds using machine learning methods
Yoldaş, Mine; Alpaslan, Ferda Nur; Büyükbingöl, Erdem; Department of Computer Engineering (2011)
This study aims to predict the binding affinity of the PCP-like compounds by means of molecular hydrophobicity. Molecular hydrophobicity is an important property which aff ects the binding affinity of molecules. The values of molecular hydrophobicity of molecules are obtained on three-dimensional coordinate system. Our aim is to reduce the number of points on the hydrophobicity surface of the molecules. This is modeled by using self organizing maps (SOM) and k-means clustering. The feature sets obtained fro...
Kaş, Aykut; Yılmazel Tokel, Yasemin Dilşad; Department of Environmental Engineering (2021-9-10)
Utilization of hyperthermophilic microorganisms was suggested to improve reaction rates and insoluble pollutant degradation and minimize the risk of contamination in bioelectrochemical systems (BESs). So far only a small group of hyperthermophilic microorganisms were identified, which show the ability to donate electrons to solid electrodes in BESs and here we present a new culture that fits to this description. The iron reducing archaeal culture Geoglobus acetivorans, originally isolated from a hydrotherma...
SASI: a generic texture descriptor for image retrieval
Carkacioglu, A; Yarman-Vural, F (Elsevier BV, 2003-11-01)
In this paper, a generic texture descriptor, namely, Statistical Analysis of Structural Information (SASI) is introduced as a representation of texture. SASI is based on statistics of clique autocorrelation coefficients, calculated over structuring windows. SASI defines a set of clique windows to extract and measure various structural properties of texture by using a spatial multi-resolution method. Experimental results, performed on various image databases, indicate that SASI is more successful then the Ga...
Citation Formats
P. Beriat, “Non-destructive testing of textured foods by machine vision,” M.S. - Master of Science, Middle East Technical University, 2009.