Automatic Detection and Value Estimation of Multiple Resistors using Image Processing Techniques

Identification of resistor values using color 
bands is a fundamental yet time-consuming 
task in electronics laboratories, especially 
when multiple resistors are present alongside 
other 
electronic 
components. 
Manual 
interpretation of resistor color codes is prone 
to error and inefficient for complex circuit 
analysis. This paper presents an image 
processing–based approach for automatic 
detection, identification, and value estimation 
of multiple resistors from a single input image. 
The proposed method employs a sequence of 
preprocessing, segmentation, morphological 
operations, and color thresholding techniques 
to isolate resistors from other components and 
accurately detect their color bands regardless 
of orientation. The system is implemented in 
MATLAB and integrated with a graphical user 
interface (GUI) for user-friendly operation. 
Experimental results using real-world images 
demonstrate reliable detection and correct 
value estimation under varying lighting 
conditions and resistor orientations. The 
proposed approach provides a low-cost, 
effective solution for automated resistor 
identification and can be extended to more 
advanced vision-based electronic component 
recognition systems.