Bautista, Gwyneth Mae I. <br/><br/>
Development of a cacao bean classification system using image processing and artificial neural network / 
by Gwyneth Mae I. Bautista and Nobie-Ann L. Quiñones. 
 - Indang, Cavite :  Cavite State University- Main Campus,  2022. 
 - xiii, 86 pages :   illustrations ;  28 cm 
<br/><br/> Design Project (Bachelor of Science in Electronics and Communications Engineering) Cavite State University. 
<br/><br/>Includes bibliographical references. 
<br/><br/>College of Engineering and Information Technology (CEIT)  College of Engineering and Information Technology (CEIT) 
<br/><br/> BAUTISTA, GWYNETH MAE., and QUIÑONES, NOBIE-ANN. Development of a<br/>Cacao Bean Classification System Using Image Processing and Artificial Neural Network.<br/>Undergraduate Project Design. Bachelor of Science in Electronics Engineering. Cavite<br/>State University, Indang, Cavite. December 2018. Adviser: Edwin R.Arboleda, DEng.<br/>Using an image processing method and an artificial neural network model, this paper<br/>outlines the development of a prototype for identifying the quality of cacao beans based on the<br/>color of its interior. The Philippine National Standards for cacao beans were used as the basis<br/>for the system's set of guidelines and standards. The prototype was able to automatically<br/>determine the classifications of hybrid Trinitario cacao beans cultivated at Dariano Cacao Farm<br/>in Silang, which is located in the province of Cavite in the Philippines. The images employed as<br/>the data samples of the project were captured using a camera in a controlled setting. The<br/>sample images that have been loaded to the system consisted of 13 cacao beans that were<br/>placed in the prototype's sample drawer.<br/>Thereafter, the photographs are transferred to the system of the prototype, which then<br/>crops each of the 13 cacao beans individually and segments the characteristics of each image<br/>based on the RGB values. Classification experiments on 260 cross-cut hybrid Trinitario cacao<br/>beans using the artificial neural network classifier yielded an overall accuracy of 91.65 percent.<br/>The findings indicate that the developed image processing technique and the Artificial Neural<br/>Network or ANN-based classifier have the potential to be used as an efficient instrument for the<br/>purpose of classifying cacao beans. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Image processing<br/>Image processing software
<br/><br/><label>Dewey Class. No.: </label>621.367  / B31 2022