Against Late Fall Hardwoods, Deep Cover scores 37/100 (), while Obskura Grom scores 57/100 ().
Based on color alignment, breakup scale, and texture density, the AI sees an approximate 20-point lean toward Obskura Grom in this particular environment.
Forloh Deep Cover and Kryptek Obskura Grom are both mixed-scale patterns, so they behave similarly from a scale point of view. Forloh Deep Cover balances micro and macro elements, while Kryptek Obskura Grom leans toward larger, macro-scale blocks, which shifts how each holds up in close cover versus more open sightlines. They are also similar in overall density, so neither one is dramatically busier or more open. Forloh Deep Cover holds a slightly broader scale spread, giving it a bit more range in tight brush and mid-distance openings.
Forloh Deep Cover vs Kryptek Obskura Grom
Forloh Deep Cover and Kryptek Obskura Grom have been analyzed using our CamoMatrix AI engine, which measures scale, density, and edge behavior directly from the flat pattern artwork. Both land in the mixed-scale category, meaning they balance fine texture with larger breakup blocks instead of living at one extreme. Density is similar, so neither pattern overwhelms the eye or leaves too much empty space. Edge style diverges: Forloh Deep Cover mixes both hard and soft edges, while Kryptek Obskura Grom leans into smoother, blended transitions. Softer edges often melt better into natural backgrounds, while harder edges can create stronger breakup in certain lighting. Kryptek Obskura Grom's numeric scale index runs slightly higher, nudging it a bit more toward macro breakup, while Forloh Deep Cover stays finer on average. Kryptek Obskura Grom lands slightly higher on the density index, adding a bit more visual texture. That can help in chaotic or brushy terrain where extra breakup is useful. Forloh Deep Cover carries more spread in our readings, which can make it more forgiving when moving between close-cover stands and semi-open edges. As always, these results come from flat pattern imagery. Real-world performance depends heavily on terrain, season, and how the garments fit and move.
This is a pattern-only comparison from flat artwork. Terrain, season, and real backgrounds will still push one or the other ahead in specific setups.
Learn how the CamoMatrix AI evaluates camouflage patterns
Defines the dominant size of shapes in the pattern.
Indicates which scale range the pattern leans toward overall.
How busy the pattern is with shapes and noise.
How hard or soft shape boundaries are.