ISO/IEC 25010 based evaluation of rice seed analyzer: a machine vision application using image processing technique

Ertie Abana, Benedict Sy


The traditional approach for quality assessment of rice is done by a human inspector manually which leads to inconsistencies and uncertainties in the assessment due to human error. To address this problem, researchers develop rice classification systems applying different methods. The development of these kinds of applications will contribute to the larger objective of maximizing the production of global food. This study introduced a new method of rice seed classification that applies hashing techniques pre-processing of image prediction and its precision rate is 93.06 percent, with a speed of 8.31 seconds per image. The developed application in this study was evaluated using ISO/IEC 25010 with total mean scores of 4.31 for functional suitability, 4.31 for performance efficiency, 4.58 for compatibility, 4.31 for usability, 4.58 for reliability, 4.51 for security, 4.28 for maintainability, and 4.42 for portability.


Computer vision; Hashing technique; Image processing; ISO/IEC 25010; Rice seed analysis

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