4. Conclusion and Future work
This method is economical than other seed analyzers and can be easily implemented with great
accuracy.It does not rely on massively looping algorithms, making it more efficient. It is
possible to determine the average area of the grain easily and can accurately count the number
of grains in the image taken. We can enhance the quality of the image. We proposed a new,
robust, fast and fully automatic algorithm. The algorithm needs no prior information or training
process. We successfully find the seed points and the segmentation results obtained are very
much accurate. There are only a small amount of pixels which are misclassified. So we can say
that this method gives better results compared to other methods.
The future work is the next stage of analyzing the seed and isolating the impurity from
the seed lot with the help of robotic hand and microcontroller. The expected output will be the
best quality seed by taking out the impurities and the impure or the seeds in parts. This will
help the agriculture industries in rectifying the quality of seed and will save the time and labor.
The future work also includes the reduction of the total execution time so that along with good
result the execution time can be reduced [20]. This technique will also provide the customers or
users, the best quality products from the agricultural industries.