Rice Grain Quality Analyzer RiceQc 1.0

Machine Vision System And Mobile Application For Analyze Rice Grain Sample

There are several types of rice are available in the market. The quality of the rice is depended on several factors. One major factor is the percentage of broken rice grains in a sample. Rice quality is primarily assessed based on physical properties such as head rice recovery, chalkiness, grain size and shape, and grain color, and premium quality traits such as aroma have extra value.In this project, we are mainly going to analyze the physical quality of the rice grains by analyzing rice grain shape and size by using android mobile application integrated with machine vision system.

Process

Capture sample image by using mobile phone camera

Convert captured image to gray scale image (RGBtoGRAY)

Threshold the image by most suitable value and convert into the binary image, the image consists only 1 and 0 s (Black and White pixels).

Find contours by using edge detection method and save contours properties into the array. Finds edges in an image using the Canny algorithm.The function finds edges in the input image and marks them in the output map edges using the Canny algorithm. The smallest value between threshold1 and threshold2 is used for edge linking. Contours are drawn by green color line. Contours can be explained simply as a curve joining all the continuous points (along with the boundary), having same color or intensity. The contours are a useful tool for shape analysis and object detection and recognition.