The Experts below are selected from a list of 18132 Experts worldwide ranked by ideXlab platform

Suman Gunasekaran - One of the best experts on this subject based on the ideXlab platform.

  • Computer Vision Technology for food quality assurance
    Trends in Food Science & Technology, 1996
    Co-Authors: Suman Gunasekaran
    Abstract:

    Computer Vision systems are being used increasingly in the food industry for quality assurance purposes. Essentially, such systems replace human inspectors for the evaluation of a variety of quality attributes of raw and prepared foods. Over the past few years, the explosive growth in both Computer hardware and software has led to many significant advances in Computer Vision Technology. Computer Vision applications range from routine inspection to complex Vision-guided robotic controls. Computer Vision Technology provides a high level of flexibility and repeatability at relatively low cost. It also permits fairly high plant throughput without compromising accuracy. Currently, Computer Vision systems are being developed as an integral part of food processing plants for on-line, real-time quality evaluation and quality control.

Danni Zhang - One of the best experts on this subject based on the ideXlab platform.

  • rapid discrimination of chinese dry cured hams based on tri step infrared spectroscopy and Computer Vision Technology
    Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2020
    Co-Authors: Danni Zhang, Xi Feng, Changhua Xu, Fuping Zheng
    Abstract:

    Abstract The aim of this study was to establish rapid and efficient methods based on a Tri-step infrared spectroscopy (Fourier transform infrared spectroscopy (FT-IR) integrated with second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR)) and Computer Vision Technology to identify and evaluate the quality of three Chinese dry-cured hams (Jinhua, Xuanwei and Rugao hams). 9 dry-cured hams (3 different quality grades of each geographical origin) had similar IR spectra. Nevertheless, they could be further discriminated visually by SD-IR and 2DCOS-IR spectra. All samples can be separated by the Computer Vision Technology incorporated with Principal Component Analysis (PCA) and Cluster analysis (CA). This study not only preliminarily verified the possibility of using Tri-step infrared spectroscopy and Computer Vision Technology to discriminate the geographical origins and quality grades of Chinese dry-cured hams, but also provided prospects of the application of infrared spectroscopy and Computer Vision Technology to authenticate other meat products.

Fuping Zheng - One of the best experts on this subject based on the ideXlab platform.

  • rapid discrimination of chinese dry cured hams based on tri step infrared spectroscopy and Computer Vision Technology
    Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2020
    Co-Authors: Danni Zhang, Xi Feng, Changhua Xu, Fuping Zheng
    Abstract:

    Abstract The aim of this study was to establish rapid and efficient methods based on a Tri-step infrared spectroscopy (Fourier transform infrared spectroscopy (FT-IR) integrated with second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR)) and Computer Vision Technology to identify and evaluate the quality of three Chinese dry-cured hams (Jinhua, Xuanwei and Rugao hams). 9 dry-cured hams (3 different quality grades of each geographical origin) had similar IR spectra. Nevertheless, they could be further discriminated visually by SD-IR and 2DCOS-IR spectra. All samples can be separated by the Computer Vision Technology incorporated with Principal Component Analysis (PCA) and Cluster analysis (CA). This study not only preliminarily verified the possibility of using Tri-step infrared spectroscopy and Computer Vision Technology to discriminate the geographical origins and quality grades of Chinese dry-cured hams, but also provided prospects of the application of infrared spectroscopy and Computer Vision Technology to authenticate other meat products.

Zhou Zheng - One of the best experts on this subject based on the ideXlab platform.

  • study of tomato leaf diseasa recognition based on Computer Vision Technology
    Journal of Anhui Agricultural Sciences, 2013
    Co-Authors: Zhou Zheng
    Abstract:

    Based on deep research of tomato foliar diseases Computer identification,a set of recognition methods for tomato disease color feature extraction,texture characteristics identification was established.The corresponding pathological characteristics and features combination model were determined,on the basis of this,the simulation research and contrast test were conducted,the results showed that the method can effectively improve the tomato leaf part disease automatic identification level.

Mahdi Ghasemi-varnamkhasti - One of the best experts on this subject based on the ideXlab platform.

  • Computer Vision Technology for real-time food quality assurance during drying process
    Trends in Food Science & Technology, 2014
    Co-Authors: Mortaza Aghbashlo, Soleiman Hosseinpour, Mahdi Ghasemi-varnamkhasti
    Abstract:

    Drying process causes many changes in the mechanical, sensorial, and nutritional properties of food products. One main challenge in the production of dried food products with acceptable shape, size, color, and texture is to monitor and control their appearance in real-time manner. Currently, there is an increasing demand for real-time approaches such as Computer Vision Technology to monitor and control the food quality indicators including shape, size, color, and texture during drying process. This note briefly describes the potential application of Computer Vision system in the monitoring and controlling of the food drying process in order to enhance the dried product quality and identifies prospects for future investigations.