Optical Coherence Tomography (OCT) is one of the most advanced, non-invasive method of eye examination. Age-related macular degeneration (AMD) is one of the most frequent reasons of acquired blindness and it has two forms. Our aim is to develop automatic methods that can accurately identify and characterize biomarkers in SD-OCT images, related to wet AMD. Detection of biomarkers can be challenging because of their variable shape, size, location and reflectivity. In this paper, we present an automatic method to localize subretinal hyperreflective material (SHRM) and pigment epithelial detachment (PED) via kernel graph cut. The proposed method is evaluated using an annotated dataset by ophthalmologists. The Dice coefficient was 0.81 (±0.11) in the case of PED and 0.77 (±0.11) for SHRM. In many cases, the ophthalmologist cannot clearly determine the exact location and extent of the biomarkers, so our achieved results are promising.