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Bipolar Magnetic Regions (BMRs) provide crucial information about solarmagnetism. They exhibit varying morphology and magnetic properties throughouttheir lifetime, and studying these properties can provide valuable insightsinto the workings of the solar dynamo. The majority of previous studies havecounted every detected BMR as a new one and have not been able to study thefull life history of each BMRs. To address this issue, we have developed anAutomatic Tracking Algorithm (AutoTAB) for BMRs, that tracks the BMRs for theirentire lifetime or throughout their disk passage. AutoTAB uses the binary mapsof detected BMRs to automatically track the regions. This is done bydifferentially rotating the binary maps of the detected regions and checkingfor overlaps between them. In this first article of this project, we provide adetailed description of the working of the algorithm and evaluate its strengthsand weaknesses by comparing it with existing algorithms. AutoTAB excels intracking even for the small BMRs (with flux $\sim 10^{20}$ Mx) and it hassuccessfully tracked 9152 BMRs over the last two solar cycles (1996--2020),providing a comprehensive dataset that depicts the evolution of variousproperties for each BMR. The tracked BMRs exhibit the well-knownlatitudinal-time distribution and 11 year cyclic variation except for smallBMRs which appear at all phases of the solar cycle and show weak latitudinaldependency. Finally, we discuss the possibility of adapting our algorithm toother datasets and expanding the technique to track other solar features in thefuture.

AutoTAB: Automatic Tracking Algorithm for Bipolar Magnetic Regions