CocoaBeansQCV

Published: 21 February 2024| Version 1 | DOI: 10.17632/sr279sf4hs.1
Contributors:
Basri Baba,
,
,
,

Description

Data for publication in Data in Brief. Cocoa Beans Quality dataset applies an image processing approach in Eight Steps. Every step implements a Computer Vision Algorithm in two condition of object classification, namely good and poor-quality cocoa beans. This dataset is already used in cocoa bean quality identification in image processing studies, so it is available for any purposes for the next project. Acquisition of the data using Video Capture and Extraction into raw image. Data was obtained from captured video using a data acquisition box device designed to connect to a conveyor. The image processing step to evaluate was based on the pre-processing approach with resizing, sharpening, RGB2HSV, Masking, Bounding Box, and Cropping Object.

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Steps to reproduce

Collect data using a conveyor with an Acquisition Box Image Capture were made in a controlled environment Extracted Image From Data Video Called Raw data in this dataset Using the image processing step to evaluate was based on the pre-processing approach with resizing, sharpening, RGB2HSV, Masking, Bounding Box, and Cropping Object. All Image processing using Computer Vision Algorthm Tools in Python Programming

Institutions

Universitas Al Asyariah Mandar, Universitas Hasanuddin Fakultas Teknik

Categories

Image Processing, Cocoa, Bean, Data Collection in Agriculture

Licence