Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/6599
Title: Grain Quality Analysis Using Digtal Image Processing
Authors: Shruti
Sharma, Prachi
Acharya, Sigma
Gupta, Pragya [Guided by]
Keywords: Matlab software
Rice quality
Issue Date: 2017
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: In the present grain-handling scenario, grain type and quality are distinguished manually by visual examination which is tiresome and imprecise. There is need for the growth of fast, correct and objective system for quality check of food grains. So for the grain type recognition and analysis an automated system is introduced . For the purification of the grains we are using color extraction property as attribute. According to the size of the grain core and existence of adulteration , grading of the rice samples was done. Nearly as soon as digital computers became available, it was realized that they could be used to process and extract information from digitalized images Due to increased expectations in quality food and safety standards there is need of correct grading, sorting of fruits and foods, or agriculture products arises. This is being evaluated through visual examination by human inspectors. This process is tiresome and time consuming. After hours of working the operator may loose concentration which in turn will affect the evaluation process. By this manual activity in terms of returns for their crop the farmers get very much affected. Hence these tasks require automation, so as to have a computer vision system as an alternative to this manual practice. Automated system of sorting food and agriculture products provides fast and hygienic inspection with computer vision. Computer vision and image processing are non destructive, correct and good methods to achieve target of grading. Machine Vision Systems are successfully used for Identification and Categorization of plants, leaves, flowers, bulk grain samples. Considerable design effort is necessary in order to perform this task of pattern recognition by machines. Categorization models were based on morphological features, color features or textural features .The region of interest was selected around the boundary of the edge after isolating the grain. The morphological features were obtained from the binary images containing only pixels of the grain edge. Grain quality is a term that refers to the quality of grain. However, what make up quality depends on the use of the grain .Quality of grain are affected by several factors which includes, growing practices, time and type of harvesting, postharvest handling, storage management and transportation practices. Grain sorting and detailing system secures that a particular lot of grain meets the required set standard customer. Quality of grains is an important requirement for today’s market, to protect the consumers from inferior products. The government imposes price control for necessary items in order to protect the consumers from black marketing and unreasonable prices. As a result some traders immorally release inferior products to the consumer market. Because of such practices there are so many poor quality grains arriving to the market day by day. These grains consists of several adulterants like stones, damaged seeds, more broken granules etc. This is often seen today in rice trade where rice of poor quality is sold without being noted. However, there is no appropriate method to identify these low quality grains in the market. Therefore, this has become a significant issue for both the consumer and the government. Hence an automated Quality analysis of the food grains could be considered helpful.
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/6599
Appears in Collections:B.Tech. Project Reports

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