Paketli gıda ürün etiketleri kullanılarak görüntü işleme ve optik karakter tanıma (OKT) tekniklerine dayalı uzman sistemin geliştirilmesi
Development of an expert system based on image processing and optical character recognition (OCR)techniques using packaged food product labels
- Tez No: 877053
- Danışmanlar: DR. ÖĞR. ÜYESİ TOLGA HAYIT, DR. ÖĞR. ÜYESİ FATMA HAYIT
- Tez Türü: Yüksek Lisans
- Konular: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Elektrik ve Elektronik Mühendisliği, Computer Engineering and Computer Science and Control, Electrical and Electronics Engineering
- Anahtar Kelimeler: Apple, Malus domestica, SSR, Label, Healty Food Choice, Nutrition, Optical Character Recognition, Images Processing Techniques, Expert System
- Yıl: 2024
- Dil: Türkçe
- Üniversite: Yozgat Bozok Üniversitesi
- Enstitü: Lisansüstü Eğitim Enstitüsü
- Ana Bilim Dalı: Elektrik-Elektronik Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Elektrik Elektronik Mühendisliği Bilim Dalı
- Sayfa Sayısı: 98
Özet
Apple (Malus domestica) is a significant pome fruit, and its genotypes are essential for breeding programs. Molecular markers, particularly the SSR (Simple Sequence Repeats) technique, are highly reliable for identifying genetic diversity and relationships among plant genotypes within a population. This study utilized SSR markers to quickly and reliably determine genetic diversity in apple genotypes. The analyses identified a total of 187 alleles across SSR loci, with allele numbers per locus ranging from 2 to 16 and an average of 8. The BC226-SCAR locus had the highest number of alleles. The number of effective alleles (Ne) varied between 1.17 (MD-EXP7SSR) and 9.11 (CH02C06), with an average of 4.67. Observed heterozygosity (Ho) among genotypes ranged from 0.16 to 1.00, with an average of 0.70, and the highest values (1.00) were found at the CH01H10, EMPC116, and HI02D04 loci. Expected heterozygosity (He) was highest at the CH02C06 and BC226-SCAR loci, with an average of 0.72. Polymorphism Information Content (PIC) values, indicating genetic diversity and marker discrimination power, ranged from 0.14 (MD-EXP7SSR) to 0.88 (CH02C06, BC226-SCAR). The UPGMA dendrogram and PCoA graph indicated that apple varieties and genotypes clustered into two main groups, further divided into four subclusters. Genetic similarity coefficients ranged from 0.14 to 0.88. The results of the dendrogram and STRUCTURE analysis were very similar, showing consistent genetic differentiation patterns across UPGMA, structure analysis, and PCoA. This study effectively characterized the genetic diversity and relationships of apple genotypes in the Yozgat region, highlighting the richness of apple genetic resources in the area and the potential for breeding programs. 2024, 40 Pages
Özet (Çeviri)
Food labels play a critical role in terms of health, safety, and legal compliance for consumers, businesses, and governments. While providing essential information about product content to consumers, labels also assist businesses in marketing their products and complying with regulatory requirements. Reading labels guides consumers in making informed food choices and lifestyle decisions, potentially improving health indicators. However, label readability may vary depending on consumers' gender, age, marital status, education level, and health condition. Factors such as font size, color tone, and complexity of information presentation can hinder effective label reading, limiting consumer access to information. With the use of expert systems, it is possible to analyze these labels more effectively and make them more understandable with the help of technologies such as optical character recognition. These developments can support consumers in making healthy choices, contributing positively to public health. In this thesis, an expert system capable of reading product label images, understanding label text, and providing recommendations based on Image Processing Techniques and Optical Character Recognition System techniques has been developed. 2024, Haziran + 80 Pages
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