  We describe the development of automated emission line detection software for
the Fiber Multi-Object Spectrograph (FMOS), which is a near-infrared
spectrograph fed by $400$ fibers from the $0.2$ deg$^2$ prime focus field of
view of the Subaru Telescope. The software, FIELD (FMOS software for
Image-based Emission Line Detection), is developed and tested mainly for the
FastSound survey, which is targeting H$\alpha$ emitting galaxies at $z \sim
1.3$ to measure the redshift space distortion as a test of general relativity
beyond $z \sim 1$. The basic algorithm is to calculate the line signal-to-noise
ratio ($S/N$) along the wavelength direction, given by a 2-D convolution of the
spectral image and a detection kernel representing a typical emission line
profile. A unique feature of FMOS is its use of OH airglow suppression masks,
requiring the use of flat-field images to suppress noise around the mask
regions. Bad pixels on the detectors and pixels affected by cosmic-rays are
efficiently removed by using the information obtained from the FMOS analysis
pipeline. We limit the range of acceptable line-shape parameters for the
detected candidates to further improve the reliability of line detection. The
final performance of line detection is tested using a subset of the FastSound
data; the false detection rate of spurious objects is examined by using
inverted frames obtained by exchanging object and sky frames. The false
detection rate is $< 1$\% at $S/N > 5$, allowing an efficient and objective
emission line search for FMOS data at the line flux level of $\gtrsim 1.0
\times 10^{-16}$[erg/cm$^2$/s].
