Against Late Fall Hardwoods, Late scores 31/100 (), while Leafy MO Obsession scores 57/100 ().
Based on color alignment, breakup scale, and texture density, the AI sees an approximate 26-point lean toward Leafy MO Obsession in this particular environment.
Cordia Late and QuikCamo Leafy MO Obsession are both mixed-scale patterns, so they behave similarly from a scale point of view. Cordia Late balances micro and macro elements, while QuikCamo Leafy MO Obsession 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. QuikCamo Leafy MO Obsession carries a wider spread in scale elements, which can help it stay effective both up close and as animals get farther out.
Cordia Late vs QuikCamo Leafy MO Obsession
Cordia Late and QuikCamo Leafy MO Obsession 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: Cordia Late mixes both hard and soft edges, while QuikCamo Leafy MO Obsession leans into smoother, blended transitions. Softer edges often melt better into natural backgrounds, while harder edges can create stronger breakup in certain lighting. QuikCamo Leafy MO Obsession also shows a higher spread index, suggesting it can maintain its breakup across a slightly broader range of shot distances. 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.