Abstarct: Industrial automation is one of the important components in industrial production, continuity, consistency and quality control of products. Increase the volume of production for each producer mean to increase in manpower, equipment and other costs.Therefore manufactures want to use automated devices always instead of human resources. Because the equipment and automated devices are quickly and more efficiently than human resources. These difference in the field of quality control is very evident and impressive and the main reason for the No fatigue of automated equipment that this reduce the error diagnostics possible to drastically of output products.This research is defect detection in DIP electronic boards using image processing. These defects are include the lack of a part, wrong direction for the parts that are important to them in orbit and the amount of electrical resistances. Portrait of a healthy board and extracted local coordinate of every part in their location first and used it for reference of the location of each part. When evaluating an input board the image provided from it, then an image by a certain sign that the board is mounted, by helping Hough algorithm will be registration to the reference board until image has two board so exactly on each other. Then to check every part used of their pre-defined local coordinates. After the image was extracted from each part, depending on the part, its features are extracted. These features include color and other shape features. By extracting these features and compare it with target features we can able to defect detection in the assembly of parts. In this study, the one of board of protective electrical of Shiraz Eramtronic Company been surveyed.30 picture of the board prepared as the databaxse is used. Extracted features and proposed methods for defect detection and contrary to all components other than the resistance of results to have a hundred percent for resistors of these results have been reduced to 85% and Because of that there are brown strips on resistance and its similarity with the board background color and resistance background color.