![]() Center for Machine Learning and Intelligent Systems |
About
Citation Policy
Donate a Data Set
Contact
View ALL Data Sets |
Source: Neeraj Julka, Research Scholar, Department of ECE, SLIET Longowal Data Set Information: The examined group comprised kernels of wheat : PBW-550U randomly selected for the experiment. High Quality Manual Visualisation of the external Kernel. It is non-destructive technique.The images were recorded using Basler Sca-17fc industrial graded color camera. The dataset can be used for tasks of classification. Attribute Information: Area, Major Axis Length, Minor Axis Length, Perimeter, Length, Width, Thinness Ratio, Aspect Ratio, Rectangular Aspect ratio, Area Ratio, Distance Max,Distance Min, Distance Ratio, Std Deviation,Mean
Relevant Papers: N. Julka and A. P. Singh, “Machine vision based detection of foreign material in wheat Kernels using shape and size descriptors,†published in International Journal of Advanced Science and Technology,, vol. 28, no. 20, pp. 736–749, 2019, ISSN : 2207-6360 Citation Request: Special thanks to Department of Electronics and Communication Engineering, Sant Longowal Institute of Engineering and Technology (SLIET), Longowal-148106, Sangrur, Punjab, India, for extending excellent technical support in the form of Lab Facilities in Machine Vision and Motion Control Lab to conclude the present investigations. |
Supported By: |
![]() |
In Collaboration With: |
![]() |