International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI-Powered Vision System for Automated Quality Grading using Image Recognition |
|---|---|
| ABSTRACT | The AI-powered vision system for automated quality grading of agricultural produce uses image recognition techniques to analyze fruits and vegetables based on their size, color, shape, and surface defects. The system captures images using a camera and processes them using image processing and machine learning algorithms. Features such as color uniformity, texture patterns, and defect detection are extracted and compared with trained models to classify produce into different quality grades. This automated grading system reduces manual effort, increases accuracy, and ensures consistent quality assessment in agricultural industries. |
| AUTHOR | D. TEJO VAMSI KRISHNA, G. SRI LAKSHMI DURGA, T. HEMA SRI, CH. KIRAN, K.G.V. NAGESWARA RAO U.G. Student, Department of ECE, SVIET Engineering College, Nandamuru, Pedana, Andhra Pradesh, India Assistant Professor, Department of ECE, SVIET Engineering College, Nandamuru, Pedana, Andhra Pradesh, India |
| VOLUME | 182 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1403130 |
| pdf/130_AI-Powered Vision System for Automated Quality Grading using Image Recognition.pdf | |
| KEYWORDS | |
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