In this study, a novel streak direction-resolving algorithm is introduced to determine the direction of the flow field for a single image frame with multiple streaks. The streak direction was resolved by varying its intensity from 100% to 50% of the total intensity of the streak image. This technique was applied to two main types of flows parallel and Hill’s vortex flows, parallel flows were divided into further two types constant velocity parallel flow and accelerating parallel flow. The purpose of using different types of flows was to test the robustness of the algorithm with easy and complex flows. The performance of the algorithm was checked by the angular deviation between the true and least-square fitted velocity vectors. The number of correct synthetic streak directions was measured with the success rate in percentage. A high success rate means low angular deviation and a high number of velocity vectors with correct direction was obtained. In this research, four different types of image formats were considered DP (double precision), 16-bit (without noise), 16-bit (1.0% noise), 16-bit (5.0% noise), and 8-bit (without noise) and the best results were obtained for DP and 16-bit image formats. The results of the parallel flows indicated a 100% streak direction success rate, Hill’s vortex was a type of complex flow therefore, the algorithm hard to resolve some streak directions due to very low velocities (less than 0.1 px (pixel)/interval) and very high-velocity gradients (greater than 52 px/interval). The observation shows that Hill’s vortex synthetic streak images were resolved with a success rate of 92.76% which means that the majority of the synthetic streaks were resolved. Experimental analysis was also done by using the PDMS microchannel setup. Intensity variation streaks were recorded with long camera exposure time and for maintaining the intensity variation, as the LED switched on maximum illumination was started, and continuous decrement in illumination was set by switching off at 50% of the total illumination intensity. The best results were achieved with a 94% success rate. Therefore, the proposed novel approach can be used with less expensive hardware for image processing with a single image frame and is useful for multiple applications.