A method of characterizing a specimen by determining the presence of interferent hemolysis, icterus, and/or lipemia, or whether the specimen is normal, HILN, comprising: capturing one or more images from multiple viewpoints of a specimen container including a serum or plasma portion, wherein the specimen container is held in a holder and some portion of the specimen container includes a label; processing the one or more images from the multiple viewpoints to provide segmentation information for each of the multiple viewpoints by determining classifications of regions for each of the multiple viewpoints; generating a semantic map from the segmentation information from each of the multiple viewpoints; selecting a synthetic viewpoint that has visibility of the serum or plasma portion, wherein the synthetic viewpoint is a viewpoint that includes the maximum number of pixels that have been classified as serum or plasma portion; identifying front view semantic data and back view semantic data for the synthetic viewpoint, wherein this identifying involves identifying the collection of pixels from the semantic map that will constitute the front view and the back view of the synthetic viewpoint; and determining HILN of the serum or plasma portion based on the front view semantic data with an HILN classifier, which HILN classifier identifies hemolysis in, based upon a classifier model being previously trained with a multitude of hemolyzed specimens of different hemolytic indices while taking into account the back view semantic data, wherein the taking into account the back view semantic data comprises - not using regions in the front view semantic data corresponding to regions that are classified as being holder in the back view semantic data, and - providing additional feature descriptors to the HILN classifier taking into account back view data before determining the HILN, and further comprising not using corresponding regions in the front view semantic data on regions that are classified as being label in the back view semantic data. capturing one or more images from multiple viewpoints of a specimen container including a serum or plasma portion, wherein the specimen container is held in a holder and some portion of the specimen container includes a label; processing the one or more images from the multiple viewpoints to provide segmentation information for each of the multiple viewpoints by determining classifications of regions for each of the multiple viewpoints; generating a semantic map from the segmentation information from each of the multiple viewpoints; selecting a synthetic viewpoint that has visibility of the serum or plasma portion, wherein the synthetic viewpoint is a viewpoint that includes the maximum number of pixels that have been classified as serum or plasma portion; identifying front view semantic data and back view semantic data for the synthetic viewpoint, wherein this identifying involves identifying the collection of pixels from the semantic map that will constitute the front view and the back view of the synthetic viewpoint; and determining HILN of the serum or plasma portion based on the front view semantic data with an HILN classifier, which HILN classifier identifies hemolysis in, based upon a classifier model being previously trained with a multitude of hemolyzed specimens of different hemolytic indices while taking into account the back view semantic data, wherein the taking into account the back view semantic data comprises - not using regions in the front view semantic data corresponding to regions that are classified as being holder in the back view semantic data, and - providing additional feature descriptors to the HILN classifier taking into account back view data before determining the HILN, and - not using regions in the front view semantic data corresponding to regions that are classified as being holder in the back view semantic data, and - providing additional feature descriptors to the HILN classifier taking into account back view data before determining the HILN, and further comprising not using corresponding regions in the front view semantic data on regions that are classified as being label in the back view semantic data.