The Determination of Ripeness Degree of Climacteric Fruits Based on Color Using Digital Image Processing / Throy Ross L. Embudo, Gio Franco L. Perez, Janine R. Sabado

By:

Embudo, Throy Ross L

Material type: Text

TextManila : Technological University of the Philippines, 2019Description: 81 pages : illustrations ; 29 cm. + 1 CD-ROM (4 3/4 in.)Content type:

text

Media type:

unmediated

Carrier type:

volume

LOC classification:

BTH QA 76 E43 2019

Dissertation note: College of Science -- Bachelor of Science in Computer Science, Technological University of the Philippines, 2019. Abstract: "The study entitled “The Determination of Ripeness degree of Climacteric fruits Based on Color using Digital Image Processing”. The objective of the study is to generate system for the detection of climacteric fruits to determine if it is ripe or unripe. It is designed to detect 3 kinds of fruits – apple, banana, and tomato. This study focuses on the improvement of development of classification model for images captured in natural environment. This study has developed a neural network (NN) model that is able to classify objects based on their surface colour. Mainly with the module of ImageAI. The SquezzeNet, ResNet, Inception V3, and DensNet are the 4 algorithm used to enhance the accuracy and prediction of the fruit and fruit’s ripeness degree. In order to support the study, the researchers undertook an evaluation to prove that the application is functioning well. This evaluation was conducted to 30 students of the College of Science. Using the ISO 9126 standards, the respondents rated the system ―Highly Acceptable." -- Author's Abstract

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Item type	Current library	Shelving location	Call number	Status	Notes	Date due	Barcode
Bachelor's Thesis COS	TUP Manila Library	Thesis Section-2nd floor	BTH QA 76 E43 2019 (Browse shelf(Opens below))	Not for loan	For Room Use Only		BTH0005294

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Thesis (Undergraduate)

College of Science -- Bachelor of Science in Computer Science, Technological University of the Philippines, 2019.

Includes bibliographical references.

"The study entitled “The Determination of Ripeness degree of Climacteric fruits Based on Color using Digital Image Processing”. The objective of the study is to generate system for the detection of climacteric fruits to determine if it is ripe or unripe. It is designed to detect 3 kinds of fruits – apple, banana, and tomato. This study focuses on the improvement of development of classification model for images captured in natural environment. This study has developed a neural network (NN) model that is able to classify objects based on their surface colour. Mainly with the module of ImageAI. The SquezzeNet, ResNet, Inception V3, and DensNet are the 4 algorithm used to enhance the accuracy and prediction of the fruit and fruit’s ripeness degree. In order to support the study, the researchers undertook an evaluation to prove that the application is functioning well. This evaluation was conducted to 30 students of the College of Science. Using the ISO 9126 standards, the respondents rated the system ―Highly Acceptable." -- Author's Abstract

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