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HARKILA'S key values, which they put in the manufacturing of all their clothes, shoes and accessories include on first place Passion, Innovation and Scandinavian attitude to every detail. 

                                                                                    

 

Guy Cramer is one of the main figures, who stays behind the new camouflage color - AXIS MSP. He is the CEO of Hyperstealth Corp. A company that works with more than 50 countries and had over 5 000 000 issued military uniforms with Hyperstealth patterns.

Hyperstealth developed the W.L.Gore Optifade hunting patterns used by Harkila. 

            

Guy Cramer began working with Harkila in 2014 to develop their HARKILA AXIS MSP (MultiSeasonal Pattern).  

DIGITAL CAMOUFLAGE: FIRST GENERATION 

Canada wore Olive Drab fatigues up until the late 1990’s when their military research showed that there is a 45 percent less chance of being detected from 50-300 meters away with their new CADPAT (Canadian Disruptive Pattern). They also found that the enemy had to be 35% closer to a soldier wearing CADPAT to detect him/her over the soldier wearing a Monotone (Olive Drab) Uniform.

Digital Camo was first experimented in Germany and Russia in the 1930s, but was first implemented in the 1980s by Canada. This new method of developing a camouflage pattern focused on addressing the weakest part of DPM, the way a pattern was visually interpreted based on detection range.

n the 1970s, US Army Lieutenant Colonel Timothy O’Neill, developed digital camouflage for the US Military. This eventually became the basis for CADPAT and later recolored for MARPAT (MARine PATtern) design which was successully implemented by the US Marines in 2001.

USMC MARPAT Woodland  Horizontal Digital Alignment

One key issue encountered with 1st Generation Digital Camouflage was found with Isoluminance, where all the camouflage colors are perceived to converge into a single overall color at a distance but cannot blend into the background environment.

    

US Army UCP (Универсален камуфлажен модел) лесно забележим / откриваем

Fractal Shapes in Nature: Fern Leaf

The fern leaf is a fractal pattern that simply repeats itself in size to form a larger scale branch. These are patterns of nature that the brain will simply ignore when processing visual information.

                      

Apply propriety fractal algorithms to create natural geometric shapes.

Human subconscious notices fractal shapes or “patterns of nature”. When the human brain analyzes a setting, it will quickly identify these natural patterns or fractal shapes and simply ignore them.

The human brain cannot process all visual information at once and needs to use a process of elimination to remove items of lesser priority, which are normally understood in the brain as common patterns. Uncommon patterns like random patterns or blobs may infactn standout as out of the ordinary, thereby increasing detection.

FRACTALS in NATURE

Fractal twig and fractal tree - Only with scale reference can we see the difference between the two. 

Proprietary Fractal Algorithems: Solution

The first step to successful fractal camouflage is based on merging common shapes using Hyperstealth’s proprietary algorithms with the correct environmental background. Then to achieve full success, this merging is then integrated into a proprietary formula to determine the optimum pattern for each target to be camouflaged.

Fractal camouflage is not about duplicating nature. It is the science of designing from the aspect of the target shape, size, and scale (such as a human) with the operational environment, vision science, geometrics, algorithms, color science, and state of the target (mobile or static).

On the two following pictures you can see a fractal camouflage that had been used on cell tower and the way it function with seasonal variences. 

     

Hunting Mimicry patterns work well in the exact environment they emulate but tend to stand out in different environments.

Colorblind Algorithems: Solution

1 in 12 men and 1 in 200 women are colorblind (approx. 4.5% of the population). Most people see three colors Red, Green, Blue, whereas most animals only perceive two colors yellow and blue. Birds can see a fourth color; Ultraviolet.

                      

How colorblind people perceive the world (bottom right) and non-colorblind (upper left) see the same environment can be very different

             

PERFORMANCE TEST OF AXIS MSP HUNTING CAMOUFLAGE. SUMMARY OF TEST PROTOCOL

The protocol used in this test is the culmination of developing methodology for camouflage evaluation from the 1970’s through the present, and has been used in dozens of evaluations for the United States government and foreign military and commercial customers. It has proven consistently sensitive to viausl performance variables, and includes measures to eliminate test bias.

This test is a photosimulation using proven “picture in picture” digitally constructed examples, high-resolution images of natural scenes simulating target detection challenges.

The trials use individual background scenes with camouflage examples inserted randomly before the analysis of pattern examples. The test trials are automated and self-administered by the Observer after a brief orientation and practice trial.

In this procedure, we measured the following performance variables:

- Mean detection (where is it) and recognition times (what is it)

- Nondetections (“misses” and false recognitions (“false alarms”)

In both cases, the performance advantage was in favor of the AXIS MSP pattern, both practically and statistically. Recorded mean detection time for 25 slides viewed by 20 Observers: 77% better performance of the AXIS MSP compared to COMP in the Mean Detection time and 53% better in the Mean Recognition time.

Recorded nondetections (Observer did not see the target before timeout 15 seconds) and false recognitions:

AXIS MSP vs COMP

Nondetected: 11 : 5

False recognitions: 72  :   62

Result: 120% Better on Nondetections and 16% Better with False Recognitions.

In conclusion: The AXIS MSP pattern outperformed the current commercial pattern significantly in all comparisons. n a case for commercial development, statistical significance is not sufficient: the difference in performance must have a practical significance (obvious to the eye). This was the case in all the conditions tested.