A simplified and powerful image processing procedures to separate the paddy of KHAW DOK MALI 105 or Thai jasmine rice and the paddy of sticky rice RD6 varieties were proposed. The procedures consist of image thresholding, image chain coding and curve fitting using polynomial function. From the fitting, three parameters of each variety, perimeters, area, and eccentricity, were calculated. Finally, the overall parameters were determined by using principal component analysis. The result shown that these procedures can be significantly separate both varieties.
The National Astronomical Research Institute of Thailand (NARIT) has developed since June 2014 an optical laboratory that comprises all the activities and facilities related to the research and development of new instruments in the following areas: telescope design, high dynamic and high resolution imaging systems and spectrographs. The facilities include ZEMAX and Solidwork software for design and simulation activities as well as an optical room with all the equipment required to develop optical setup with cutting-edge performance.
The current projects include: i) the development of a focal reducer for the 2.3 m Thai National Telescope (TNT), ii) the development of the Evanescent Wave Coronagraph dedicated to the high contrast observations of star close environment and iii) the development of low resolution spectrographs for the Thai National Telescope and for the 0.7 m telescopes of NARIT regional observatories. In each project, our activities start from the instrument optical and mechanical design to the simulation of the performance, the development of the prototype and finally to the final system integration, alignment and tests. Most of the mechanical parts are manufactured by using the facilities of NARIT precision mechanical workshop that includes a 3-axis Computer Numerical Control (CNC) to machine the mechanical structures and a Coordinate Measuring Machine (CMM) to verify the dimensions.
In this paper, we give an overview of the optical laboratory activities and of the associated facilities. We also describe the objective of the current projects, present the specifications and the design of the instruments and establish the status of development and we present our future plans.
We previously showed that a combination of image thresholding, chain coding, elliptic Fourier descriptors, and artificial neural network analysis provided a low false acceptance rate (FAR) and a false rejection rate (FRR) of 11.0% and 19.0%, respectively, in identify Thai jasmine rice from three unwanted rice varieties. In this work, we highlight that only a polynomial function fitting on the determined chain code and the neural network analysis are highly sufficient in obtaining a very low FAR of < 3.0% and a very low 0.3% FRR for the separation of Thai jasmine rice from Chainat 1 (CNT1), Prathumtani 1 (PTT1), and Hom-Pitsanulok (HPSL) rice varieties. With this proposed approach, the analytical time is tremendously suppressed from 4,250 seconds down to 2 seconds, implying extremely high potential in practical deployment.
Instead of considering only the amount of fluorescent signal spatially distributed on the image of milled rice grains this
paper shows how our single-wavelength spectral-imaging-based Thai jasmine (KDML105) rice identification system can
be improved by analyzing the shape and size of the image of each milled rice variety especially during the image
threshold operation. The image of each milled rice variety is expressed as chain codes and elliptic Fourier coefficients.
After that, a feed-forward back-propagation neural network model is applied, resulting in an improved average FAR of
11.0% and FRR of 19.0% in identifying KDML105 milled rice from the unwanted four milled rice varieties.
This paper combines multispectral imaging and simple image processing techniques for the non-destructive
identification of Thai rice breeds. Especially, we exploit only two fluorescent wavelengths in a 500-580 nm wavelength
band and utilize simple image thresholding, blob filtering, and blob analysis techniques in order to identify 8 different
Thai rice breeds. Other key features include no waste produced and fast identification time. In our experimental study,
UVC light is used as our exciting light, a liquid crystal tunable optical filter is used for our wavelength selection, and a
camera with 644×488 active pixels is used to capture desired wavelength images. Milled rice grains from 8 different
Thai rice breeds having similar size and shape are tested. There is also one glutinous rice breed in our experiment. Our
experimental result shows that by suitably applying image thresholding, blob filtering, and blob analysis to fluorescent
images, all Thai rice breeds can be effectively identified.
Because Thai Hom Mali, also known as Thai Dawk Mali (KDML105), rice is very popular and its price is high
compared to other Thai rice varieties, there is an increase in mixing KDML105 milled and unmilled rice grains with
other rice varieties, leading to unqualified KDML105 milled rice products for export and unqualified KDML105
unmilled rice seeds for next plants. Instead of using traditional time- and energy- consuming procedures such as alkaline
spreading value and pasting property tests, this paper proposes a fast refractometry-based method to analyze ground
milled rice grains dissolved in an alkaline solution. Our idea comes from the fact that due to differences in the amount of
amylose content in each rice variety, the refractive index of the milled rice powder dissolved in an alkaline solution can
be used to distinguish the desired KDML105 rice from others. In our approach, only 0.1 grams of milled rice powder is
ground, it is then dissolved in a 10% potassium hydroxide, and its refractive index is investigated. Our experiment using
a temperature-controlled optical refractometer and four Thai rice varieties (KDML105, Pathumthani1, Chainat1, and a
Thai sticky rice) shows that the milled KDML105 rice can be distinguished from the remaining three rice varieties with a
total false error rate of 6.7% and the required measurement time of < 20 seconds. Key advantages include simplicity,
moderate accuracy, and less waste produced.
As the Thai Dawk Mali (KDML105) rice variety is popular due to its high sensory after cook, there is an increase in
mixing the KDML105 rice with other rice varieties that leads to unqualified KDML105 milled rice products for export
and unqualified unmilled rice seeds for next plants. Instead of using traditional time consuming methods based on the
disintegration of the rice kernel in an alkali solution and the inspection of rice cooked in boiling water, this paper
proposes to analyze the milled rice powder dissolved in our alkali solution via a spectroscopic method. In our study, 0.1
g, 0.2 g, and 0.3 of milled rice powder from four Thai rice varieties, i.e., KDML105, Pathumthani1, Chainat1, and RD6,
are selected. Then each milled rice sample is ground and then dissolved in a 10% potassium hydroxide (KOH) solution.
At the specified minutes of dissolution, the relative optical transmission spectrum of the milled rice solution in a 500-800
nm wavelength is measured and only its first derivative is used for the identification of the KDML105 milled rice. We
find that the use of 0.10 g of the milled rice powder dissolved in our KOH solution for 10 minutes provides the lowest
false rejection rate of 15%, indicating that we have a faster approach with less amount of waste produced. With the 0.2-g
milled rice powder, 5 minutes of dissolution is needed but with a slightly higher false rejection rate of 18.3%.
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