We introduce a method for producing a galaxy sample unbiased by surface brightness and stellar mass, by selecting star-forming galaxies via the positions of core-collapse supernovae (CCSNe). Whilst matching $sim$2400 supernovae from the SDSS-II Supernova Survey to their host galaxies using IAC Stripe 82 legacy coadded imaging, we find $sim$150 previously unidentified low surface brightness galaxies (LSBGs). Using a sub-sample of $sim$900 CCSNe, we infer CCSN-rate and star-formation rate densities as a function of galaxy stellar mass, and the star-forming galaxy stellar mass function. Resultant star-forming galaxy number densities are found to increase following a power-law down to our low mass limit of $sim10^{6.4}$ M$_{odot}$ by a single Schechter function with a faint-end slope of $alpha = -1.41$. Number densities are consistent with those found by the EAGLE simulations invoking a $Lambda$-CDM cosmology. Overcoming surface brightness and stellar mass biases is important for assessment of the sub-structure problem. In order to estimate galaxy stellar masses, a new code for the calculation of galaxy photometric redshifts, zMedIC, is also presented, and shown to be particularly useful for small samples of galaxies.
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