An extensive survey of extragalactic objects with accurate distances is difficult to perform. Distance at that scale is commonly found with redshift and most easily identified with spectroscopic observations, which are time intensive. This is especially a concern when surveying for the elusive, possibly non-existent dwarf galaxies in the centers of voids, whose light would be so faint that a spectroscopic survey to find them would be unreasonably time consuming. Photometric methods to calculate redshift could provide a much quicker way to find distance, but the photometric methods used thus far are characterized by large errors that make them unusable for research on nearby voids. I have been testing two photometric redshift methods that have been recently developed: the Gaussian filter method and the ramp filters method. The Gaussian filter method isolates objects that have emission within the bandpass of the Gaussian filters. Spectroscopic follow-up observations of objects observed with the Gaussian filter method confirmed that 41.9% of the objects identified by the method actually had emission lines within the bandpass of the filters, which is more than a random sampling where only 7% of galaxies had emission within that wavelength range. Assuming that all the lines identified were Hα, the photometric redshift calculated from the Gaussian filter observations had an error of 945 km/s (or 430 km/s by excluding one outlier). Ramp filter observations of objects with SDSS redshifts provided a way to identify redshift with an error of 641.8 km/s. These errors are about an order of magnitude less than other redshift methods. These methods show promise for uses in observational cosmology, specifically extragalactic survey work and searching for void galaxies.