Assignment –Visualization

Challenge:

In food processing industries its time consuming process and more man power required to detect

irregular shapes of potatoes.  Fast and accurate computer-based machine vision system for

detecting irregular potatoes in real-time.

Selection:

Supported algorithms were specifically developed and programmed for image acquisition and

processing, controlling the whole process, saving the classification results and monitoring the

progress of all operations.

Application

 Agricultural

 Food Processing Industries

Insight & approach:

A database of images was first formulated from potatoes with different shapes and sizes, and then

some essential geometrical features such as perimeter, centroid, area, moment of inertia, length

and width were extracted from each image. Also, eight shape parameters originated from size

features and Fourier transform were calculated for each image in the database. All extracted shape

parameters were entered in a stepwise linear discriminant analysis to extract the most important

parameters that most characterized the regularity of potatoes. Based on step-wise linear

discriminant analysis, two shape features (roundness and extent) and four Fourier-shape

descriptors were found to be effective in sorting regular and irregular potatoes.


Assignment – Visualization Challenge : In food processing industries its time consuming process and more man power required to detect irregular shapes of potatoes . Fast and accurate computer - based machine vision system for detecting irregular potatoes in real - time . Selection : Supported algorithms were specifically developed and programmed for image acquisition and processing , controlling the whole process , saving the classification results and monitoring the progress of all operations . Application  Agricultural  Food Processing Industries Insight & approach : A database of images was first formulated from potatoes with different shapes and sizes , and then some essential geometrical features such as perimeter , centroid , area , moment of inertia , length and width were extracted from each image . Also , eight shape parameters originated from size features and Fourier transform were calculated for each image in the database . All extracted shape parameters were entered in a stepwise linear discriminant analysis to extract the most important parameters that most characterized the regularity of potatoes . Based on step - wise linear discriminant analysis , two shape features ( roundness and extent ) and four Fourier - shape descriptors were found to be effective in sorting regular and irregular potatoes .