scholarly journals An Economical Design of Automatic Rice Grading using Image Processing

Product quality inspection is a crucial step in the production line of rice industries. To maintain the quality and enhance the inspection methodology, the challenge is to scrutinize rice grain individually over entire batch for escalating the yield. The conventional method used in rice industries is to examine the quality of rice grains manually. The decisions made by human quality control inspectors may be affected by external influences like fatigue, exhaustion or stress which causes non uniformity in evaluation procedure and generate the high probability of errors. The major drawback of the manual inspection comprises high labor content and expenditures. This research paper provides a cost effective design solution to overcome the described limitations by developing a system which helps in sorting rice and eliminate the manual examination. For attaining the automatic grading of rice, the image processing technique is applied which help to sort defected rice grain from the entire batch of rice grains. The system has been developed on MATLAB which helps in the inspection process and its graphical user interface provides information of rice grains in three different quality based categories which sorted on the basis of size and colors. To identify the defected grains, the multilevel threshold method of image processing has been used. The proposed design also helps to determine the quantity of defected rice grains by evaluating the quantity of discolored grains and to identify the size of the rice grain, the geometrical features extracted for each individual rice grain are used to estimate the length

Author(s):  
Kesavan Suresh Manic ◽  
Imad Saud Al Naimi ◽  
Feras N. Hasoon ◽  
V. Rajinikanth

A considerable number of heuristic procedures are widely implemented to evaluate biomedical images. This chapter proposes an evaluation procedure for digital bitewing radiography (DBR) images using the Jaya algorithm. The proposed procedure implements an image processing technique by integrating of the multi-thresholding and segmentation procedure to extract the essential tooth elements recorded with DBR. In this paper, 80 dental x-ray images are considered for the evaluation. The performance of the proposed procedure is confirmed using a relative assessment between the extracted section and its corresponding ground-truth. The results of this study confirm that, for most of the DBR cases, the proposed approach offers better values of picture likeliness measures. Hence, this technique can be considered for the automated detection of tooth elements from the DBR obtained from clinics.


Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.


Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.


Author(s):  
Yashpal Jitarwal ◽  
Tabrej Ahamad Khan ◽  
Pawan Mangal

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.


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