Fitting a Pineapple Model for Automatic Maturity Grading

Kaewapichai, Watcharin; Kaewtrakulpong, Pakorn; Prateepasen, Asa; Khongkraphan, Kittiya

doi:10.1109/icip.2007.4378940

Cited by 10 publications

(6 citation statements)

References 5 publications

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“…It is recognized as the integration of optical sensing and computing processes in order to evaluate the datasets automatically (Brosnan & Sun, 2004). Kaewapichai et al (2007) developed pineapple scale models to determine automatic detection for maturity grading of the fruit. Based on the model, a modified algorithm was used to accurately fit the scale model using pineapple features including boundary, internal area, and petal scale.…”

Section: Non-destructive Approaches For Quality Evaluation Of Pineapplementioning

confidence: 99%

An overview of non-destructive approaches for quality determination in pineapples

2020

JAFE

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Pineapple is one of the healthful and popular tropical fruits in the world. The quality determination of pineapples was mostly evaluated by human inspection which is inconsistent and subjective. The increasing demand for pineapples creates more opportunities for the advancement of rapid and non-destructive approaches to seek quality evaluation of the fruit. This review gives an overview of the non-destructive approaches on the quality determination of pineapples including computer vision, imaging-based approaches, spectroscopy-based approaches, acoustic impulse, and electronic nose. The advance of non-destructive techniques to evaluate the quality of pineapple can produce better yield and improve postharvest handling. This paper also highlighted the recent works on the quality determination of pineapple fruit using non-destructive approaches along with the abundant information that can be explored for real-time purposes. This information is expected to be useful not only for pineapples growers/industries but also for other agro-food commodities.

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Section: Non-destructive Approaches For Quality Evaluation Of Pineapplementioning

confidence: 99%

An overview of non-destructive approaches for quality determination in pineapples

2020

JAFE

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“…An overview of these models is presented in Section 3. In a recent study (Kaewapichai et al, 2007) the phyllotactic model was used to fit the arrangement of the scales on a pineapple.…”

Section: Related Workmentioning

confidence: 99%

Using Phyllotaxis for Date Palm Tree 3d Reconstruction From a Single Image

Dror

Shimshoni

2009

Proceedings of the Fourth International Conference on Computer Vision Theory and Applications

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Phyllotaxis is the study of the morphological order of plants. Remarkably, in spite of the overwhelming diversity of plant morphology, there are common patterns that link a wide variety of species. The date palm, having a phyllotactic order, possesses a simple, repetitive model. Only a small number of parameters are needed to represent the phyllotactic order of the date palm. This a priori knowledge we have on the date palm can help in the 3D reconstruction of the tree and can even make it possible to reconstruct a 3D model from only one image. The proposed algorithm receives as input a single image of the date palm. Upon image acquisition, the algorithm proceeds to search for, and locate, the trunk followed by a few prominent leaves. From the location of the prominent leaves the algorithm proceeds to calculate tree model parameters, which can then be used to search for additional, neighboring, leaves. Complete 3D reconstruction is achieved by utilizing the calculated tree model parameters and by the known location of the leaves on the 2D image.

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“…The external quality such as size, weight and external appearances are considered. While, internal quality evaluates for food chemicals, texture and color [1], [2]. Pineapple has to be graded to ensure the best quality before it is distributed to consumers or canning process.…”

Section: Introductionmentioning

confidence: 99%

“…The scale model includes boundary, internal area and petal part of the scale. The developed model performed accurately fit to pineapple skins in the experiment and classification features of the fruit can be extracted [2]. A real-time pineapple matching system by using stereo vision technique and speeded-up robust features algorithm was developed.…”

Section: Introductionmentioning

confidence: 99%

Pineapple quality grading using image processing and fuzzy logic based on Thai Agriculture Standards

Suksawat

Komkum²

2015

2015 International Conference on Control, Automation and Robotics

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This research aimed to create a tool for pineapples quality grading according to the standard weight and size of Thai Agricultural Commodity Food Standard. The standard weights of pineapple are divided into 10 levels (A-J) and the standard sizes of pineapple are categorized into two classes (class I and class II). The developed tool consists of hardware components and a grading software program. The control light source box was constructed for camera and load cell installation to capture pineapple image and measure pineapple weight, respectively. The obtained image was sent to software program to change colors of the image into gray scale and to reduce noises in the image. The clearly edges of the image were employed to compute size of a pineapple and the data were transferred to fuzzy system. The inputs of fuzzy system determined the size and weight of pineapple which used to establish twenty fuzzy rules. The experiments performed by random selection size and weight of three pineapple kinds including Nanglae, Sriracha, Phuket. The experimental results reveal that classification of pineapple by the created tool exhibited high accuracy of size and weight detection equaled 87.5%. The average relative error performed 2.30% and 5.24% of size and weight, respectively.

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Fitting a Pineapple Model for Automatic Maturity Grading

Cited by 10 publications

References 5 publications

An overview of non-destructive approaches for quality determination in pineapples

An overview of non-destructive approaches for quality determination in pineapples

Using Phyllotaxis for Date Palm Tree 3d Reconstruction From a Single Image

Pineapple quality grading using image processing and fuzzy logic based on Thai Agriculture Standards

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