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.