Image acquisition techniques for assessment of legume quality

Mahajan, Shveta; Das, Amitava; Sardana, Harish Kumar

doi:10.1016/j.tifs.2015.01.001

Cited by 78 publications

(36 citation statements)

References 75 publications

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“…The results demonstrate that online monitoring for water quality information could be 12 Journal of Sensors accurately acquired and predicted by using the remote wireless system. Mahajan et al [161] reported that agriculture is noteworthy that computer vision applications have grown due to reduced equipment costs, increased computational power, and increasing interest in nondestructive food assessment methods. The use of these techniques presents advantages when compared with traditional methods based on manual work; however, there are still some challenges to be overcome.…”

Section: Application Of Artificial Intelligence Techniques In Agriculmentioning

confidence: 99%

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

et al. 2018

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In recent years, intelligent sensor techniques have achieved significant attention in agriculture. It is applied in agriculture to plan the several activities and missions properly by utilising limited resources with minor human interference. Currently, plant cultivation using new agriculture methods is very popular among the growers. However, the aeroponics is one of the methods of modern agriculture, which is commonly practiced around the world. In the system, plant cultivates under complete control conditions in the growth chamber by providing a small mist of the nutrient solution in replacement of the soil. The nutrient mist is ejected through atomization nozzles on a periodical basis. During the plant cultivation, several steps including temperature, humidity, light intensity, water nutrient solution level, pH and EC value, CO2concentration, atomization time, and atomization interval time require proper attention for flourishing plant growth. Therefore, the object of this review study was to provide significant knowledge about early fault detection and diagnosis in aeroponics using intelligent techniques (wireless sensors). So, the farmer could monitor several paraments without using laboratory instruments, and the farmer could control the entire system remotely. Moreover, the technique also provides a wide range of information which could be essential for plant researchers and provides a greater understanding of how the key parameters of aeroponics correlate with plant growth in the system. It offers full control of the system, not by constant manual attention from the operator but to a large extent by wireless sensors. Furthermore, the adoption of the intelligent techniques in the aeroponic system could reduce the concept of the usefulness of the system due to complicated manually monitoring and controlling process.

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Section: Application Of Artificial Intelligence Techniques In Agriculmentioning

confidence: 99%

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

et al. 2018

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“…Nuclear magnetic resonance (NMR) is based on the absorption and emission of energy in the radio frequency range from 60 to 1000 MHz of the electromagnetic spectrum (Mahajan et al 2015). The principle of this technique is that many nuclei are included in a sample and all nuclei are electrically charged; when an object is placed in a strong magnetic field, the hydrogen nuclei spins become aligned parallel and anti-parallel to the field.…”

Section: Nuclear Magnetic Resonance Imagingmentioning

confidence: 99%

Agricultural Product Authenticity and Geographical Origin Traceability

Zhao

Nakano

2018

JARQ

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As the security of agricultural products has become a serious issue faced by people worldwide in recent decades, measures for an effective supervision system for agricultural product quality and safety are continuously being developed. In such a system, the assessment of agricultural product authenticity and geographical origin traceability could play a very important role. Recently, researchers have been focusing on some successful techniques, including the stable isotopic technique, compositional analysis technique, spectroscopic technique, and sensor technology. The benefits from advances made in spectroscopy and imaging technology have facilitated the development of imaging spectrometry techniques that offer such advantages as being nondestructive, rapid, and requiring minimal to no sample preparation. This paper discusses several nondestructive technologies used for the assessment of agricultural product authenticity and geographical origin traceability, with a special focus on the nondestructive technology of imaging using an electromagnetic spectrum for agricultural product safety and quality. It specifically discusses the technology of ultraviolet imaging, hyperspectral imaging, fluorescence spectrometry, nuclear magnetic resonance, and terahertz spectroscopy according to different wavelengths and frequency of this electromagnetic spectrum. Although the application of nondestructive measurements performed using the electromagnetic spectrum for identifying agricultural product authenticity and geographical origin traceability is increasing along with advanced technology and lower equipment costs, the accuracy of such measurements must still be improved and the advantages in practical applications need to be determined.

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“… Equivalent diameter: The diameter of circle with the same area of the fastener [9]. (4) Where A is the area of the equivalent circle of the fastener.…”

Section: Shape-based Feature Extraction Techniquementioning

confidence: 99%

A Comparative Analysis of Shape Based and Zernike Moment Feature Extraction Techniques for Fasteners Recognition Using Neural Network

Hashim¹,

Jalil²,

Diyanah³

2016

Sixth International Conference on Advances in Computing, Electronics and Electrical Technology - CEET 2016

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Abstract-This paper presents a Comparative Analysis of Shape-based and Zernike moment Feature Extraction Techniques for Fastener Recognition. There a nine features extracted using shape-based technique and 64 moments used in Zernike feature extraction technique. For Zernike moment technique, the 64 moments are divided into 3 groups. The first group is the lower order moments, the second group is the higher order moments and the third group is the combination between the lower order group and the higher order group. The processes taken in the recognition are image acquisition, pre-processing, segmentation, feature extraction, and classification. The segmentation process is carried out by using adaptive filter and the classification process employed artificial neural network. The final result from this experiment is that shape-based technique has a better classification result of about 84.93% correct recognition compared to Zernike moment technique which is about 51.53% (combined group).

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Image acquisition techniques for assessment of legume quality

Cited by 78 publications

References 75 publications

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

Agricultural Product Authenticity and Geographical Origin Traceability

A Comparative Analysis of Shape Based and Zernike Moment Feature Extraction Techniques for Fasteners Recognition Using Neural Network

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