The spatial segregation of Muslims in urban India is central to their social, economic, and political marginalization. However, the quantitative characterization of Muslim segregation has suffered from the lack of readily available demographic data at high spatial and temporal resolutions. This paper demonstrates the feasibility of accurately quantifying Muslim segregation in urban India using the latest electoral rolls data from Bengaluru (a megapolis of over 13 million residents) and an improved open-source algorithm to identify Muslim names. Our approach provides significant improvements over past efforts in this regard. We introduce two new metrics (diversity and local divergence) to account for substantial intra-city variation in the spatial segregation of Muslims. Our analysis suggests that the threefold ghetto-enclave-mixed taxonomy that the extant literature has quantified for entire towns can be found within large urban agglomerations such as Bengaluru. Our quantitative framework for Muslim segregation helps uncover the complex relationship between segregation and the ghettoization of Muslims in urban India. Our measurement framework uses publicly available data and can be applied to study segregation patterns across urban India.