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].
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