Quality inspection of cocoons using X-ray imaging technique

Quality of cocoons determined by its silk content which is directly related with the market value. Silk is broadly used in textiles and it is costly too. Farmers are selling the cocoons in a bulk with an average market value to the yarn producers. Presently, the quality of cocoons is verified by visualizing the color, size, shape and feeling its solidity on pressing by fingers of our hand. These manual inspections sometimes create dissatisfaction among the buyers and sellers. Sometimes, the sellers (farmers) are duped by the clever buyers. In other method, the silk content is estimated by taking the average raw cocoon shell weight after cutting the cocoon and removing the pupa from it. This approach is destructive, time consuming, expensive and laborious also. In this paper, X-ray imaging technique has been explored to estimate the silk content and determine the quality of cocoons. Firstly the images of the cocoons are captured using standard X-Ray imaging setup. Then the images are enhanced using digital image processing techniques. Finally, different dimensional features are extracted using image analysis techniques. A new method for estimation of the silk content has been proposed using the GRNN (General Regression Neural Network). Quality of the cocoons has been evaluated using unsupervised artificial neural network technique known as SOM (Self Organizing Map) which produces the different classes of quality grades of cocoons. In this experiment, we have considered five classes - good, medium, bad, dead pupa and un-identified quality. Total 49 no of cocoons have been used for the experimentation. The result shows that using GRNN the estimation of silk content is quite helpful with a fair level of accuracy. Using SOM technique, quality of cocoons has been determined and the result is validated with the manual inspection method. Both this approach of estimating the silk content and determining the quality of cocoons opens new possibilities in the field of automati- , non-destructive technique for price appraisal of cocoons.