Method and system for identification and classification of different grain and adulterant types

A system for grain grading analysis, the system comprising:

• a memory storing instructions;
• one or more Input/Output (I/O) interfaces;
• and
• one or more hardware processors coupled to the memory via the one or more I/O interfaces, wherein the one or more hardware processors are configured by the instructions to:
• preprocess an image, received for the grain grading analysis for a grain type, to enhance image quality, wherein the image comprises a sample element mixture comprising a plurality of elements and a reference object, and wherein the preprocessing comprises iterating the image through an image enhancement process till the image satisfies a quality criteria;
• process the preprocessed image by performing resizing, denoising, and Gaussian blurring to obtain a processed image;
• determine a plurality of morphological features of the plurality of elements in the processed image by:
• a) performing background elimination using image segmentation and inpainting operation, followed by contour detection on the processed image to obtain a contour plot of each of the plurality of elements and the reference object in the processed image;
• b) determining i) a calibration factor in terms of pixel per metric for a length, a width and a height, and ii) an aspect ratio to predetermined weight mapping tables of a plurality of reference objects, a plurality of grain types and a plurality of varieties of the plurality of grain types;
• and
• c) determining the plurality of morphological features of each of the plurality of elements using the contour plot and the calibration factor, wherein the morphological features comprise a perimeter, a width, a height, and an aspect ratio;
• confirm whether the sample mixture is of the grain type by determining whether at least a predefined number of elements among the plurality of elements belong to the grain type, wherein the grain type is identified by binning each of the plurality of elements in accordance with the element aspect ratio into a plurality of bins and checking whether one or more elements associated with a bin, among the plurality of bins, satisfy a kernel aspect ratio range predefined for the grain type;
• differentiate the plurality of elements, post confirming the sample element mixture is of the grain type, wherein the differentiation is based on a lower threshold and an upper threshold of an Inter Quartile Range (IQR) of a perimeter metric corresponding to the perimeter of each of the plurality of elements to segregate the plurality of elements as:
• a) a first set of elements having lower size impurity in the sample element mixture,
• b) a second set of elements having a target grain perimeter range identified for the grain type, and
• c) a third set of elements having a higher size impurity;
• and
• perform:
• a) identification of a variety of the grain type, from among the plurality of varieties by binning the second set of elements into a plurality of bins based on the aspect ratio, wherein the aspect ratio associated with a max bin among the plurality of bins that has maximum number of elements from the second set of elements indicates the variety of the grain type being graded in accordance with a predefined aspect ratio to variety mapping;
• and
• b) calculation of a total adulteration percentage for the variety based on number of elements in the max bin and number of elements in the first set of elements and the second set of elements.

One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:

• preprocessing an image, received for the grain grading analysis for a grain type, to enhance image quality, wherein the image comprises a sample element mixture comprising a plurality of elements and a reference object, and wherein the preprocessing comprises iterating the image through an image enhancement process till the image satisfies a quality criteria;
• processing the preprocessed image by performing resizing, denoising, and Gaussian blurring to obtain a processed image;
• determining a plurality of morphological features of the plurality of elements in the processed image by:
• a) performing background elimination using image segmentation and inpainting operation, followed by contour detection on the processed image to obtain a contour plot of each of the plurality of elements and the reference object in the processed image;
• b) determining i) a calibration factor in terms of pixel per metric for a length, a width and a height, and ii) an aspect ratio to predetermined weight mapping tables of a plurality of reference objects, a plurality of grain types and a plurality of varieties of the plurality of grain types;
• and
• c) determining the plurality of morphological features of each of the plurality of elements using the contour plot and the calibration factor, wherein the morphological features comprise a perimeter, a width, a height, and an aspect ratio;
• confirming whether the sample mixture is of the grain type by determining whether at least a predefined number of elements among the plurality of elements belong to the grain type, wherein the grain type is identified by binning each of the plurality of elements in accordance with the element aspect ratio into a plurality of bins and checking whether one or more elements associated with a bin, among the plurality of bins, satisfy a kernel aspect ratio range predefined for the grain type;
• differentiating the plurality of elements, post confirming the sample element mixture is of the grain type, wherein the differentiation is based on a lower threshold and an upper threshold of an Inter Quartile Range (IQR) of a perimeter metric corresponding to the perimeter of each of the plurality of elements to segregate the plurality of elements as:
• a) a first set of elements having lower size impurity in the sample element mixture,
• b) a second set of elements having a target grain perimeter range identified for the grain type, and
• c) a third set of elements having a higher size impurity;
• and
• performing:
• a) identification of a variety of the grain type, from among the plurality of varieties by binning the second set of elements into a plurality of bins based on the aspect ratio, wherein the aspect ratio associated with a max bin among the plurality of bins that has maximum number of elements from the second set of elements indicates the variety of the grain type being graded in accordance with a predefined aspect ratio to variety mapping;
• and
• b) calculation of a total adulteration percentage for the variety based on number of elements in the max bin and number of elements in the first set of elements and the second set of elements.