Mixing is often a challenge in small scales and substantial research effort is focused on designing high performance micromixers. Active micromixers use various forces to enhance mixing efficiency. Among these, magnetic forces are often preferred as they are non-contact and do not require manufacturing of small moving parts in the microchannel. Laser-based diagnostic tools have great potential in providing multi-parameter information in microfluidics research on mixing. In this work, we extract velocity, concentration and interface front information from a single image pair from a magnetic micromixer undergoing labyrinthine (fingering) instability. The experiments were performed using a MicroPIV system with stroboscopic LED illumination. Velocity information from particle displacements are computed using Least Squares Matching (LSM) and compared with previously published results using Adaptive Cross Correlation (ACC). It turns out that LSM is less sensitive to image contrast; and able to extract most of the useful velocity information from the raw images compared to the processed images. This makes LSM an important global tool for PIV analysis where image pre-processing can be avoided completely, for example in industrial mixing applications. The use of image processing functions proves to be essential in multi-parameter microfluidics: Concentration measurements are performed using absorption imaging after removal of particles using a series of low-pass filters. Results for interface front detection using various other image processing functions are also presented.