Identification of Resistor Types Using Extreme Learning Machine Algorithms and Morphological Operation

Electronic components are the basic elements to form a series of electronic devices that usually used in everyday life. For someone who studies field electricity, knowledge electrical is an important thing. One whose use most often found circuits resistor. However, some people do not know about these types resistors. Especially for or student will learn components. This study aims develop image processing system can identify transistor type images using Extreme Learning Machine (ELM) algorithm. algorithm performs integrated learning through special feedforward perceptron which has one hidden layer. In order ELM work properly, information features contained object be identified needed. So, this combined with morphological characteristics parameters such as area, perimeter, eccentricity, major axis length, and minor length. Based on parameters, obtained input identification process. At evaluation stage, precision value was 87%, recall 84.47% accuracy 85.5%.