Title |
Research and development of automatic visual inspection system of wooden dowels / |
Translation of Title |
Medinių kotelių vizualinės patikros sistemos kūrimas ir tyrimas. |
Authors |
Alwar, Rajagopal Dhanasingh Madhumadi |
Full Text |
|
Pages |
75 |
Keywords [eng] |
wooden dowels ; machine vision ; color space ; neural network ; MATLAB |
Abstract [eng] |
The purpose of this study was mainly due to a problem statement provided by a company manufacturing small wooden dowels. A visual inspection system to identify the presence of defect in the stick will be required. The focus will be in the algorithm development and proposal for the system design will be given. The previous literature assumed a particular color space to be the best and worked on selecting the effective features that could be extracted from them. The main focus of this thesis is to identify the best color space that could be used for all defect detection and grading system related to wood. Not well studied Neural Network structure for wood defect application will be used as the classifier and the reaction of the number of inputs and number of hidden units to produce effective results was studied At first a simple and effective algorithm for finding the defect was developed. This algorithm was tested with different colour space for different number of hidden neurons. The effectiveness of each color space was found and the best color space was chosen. The best NN structure and the outputs for different neuron numbers was also found. There is no exact rule for selecting the number of neurons so far, so based on the previous assumptions and studies the neurons were selected and checked if the assumptions holds good in our case. The system was designed based on the requirements and the setup was made. The algorithm part was developed with MATLAB. From the experiments the effective color space RGB and YCbCr produced results with 96% accuracy and the combination of them produced about 99% accuracy for the chosen neuron numbers. The not very well studied NN structure was studied. Algorithm was made effective by minimizing the time for processing as much as possible. |
Dissertation Institution |
Kauno technologijos universitetas. |
Type |
Master thesis |
Language |
English |
Publication date |
2015 |