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I-CUBE offers turnkey systems custom designed to be "out of the box" solutions for specific customer applications, priced no higher than the cost of individual components.
  • Imaging products are chosen to both meet specific customer application requirements AND to work seamlessly together
  • Computer system components are selected to optimize compatibility and performance
  • All software, hardware, and drivers are installed and the system tested to ensure optimal performance
  • Systems are tested and shipped complete, enabling the customer to simply set it up upon receipt and begin productive work almost immediately - we even include cabling diagrams and custom setup instructions when applicable
  • Customers make only one call for technical support, eliminating integration headaches and finger pointing among component vendors.
    Measuring of fibre orientation in nonwovens using image processing
    By : S. Hariharan, S. A. Sathyakumar, P. Ganesan


    The standardized index of dispersion was tested on real as well as simulated patterns by dividing the patterns into quadrats of different areas ranging from 2 mm2 to 100 mm2. For a given quadrat size and number, the same image was sampled multiple times by shifting the position of horizontal grid lines by a known amount (10% of height) in the downward direction (CD) while keeping the column positions constant. This was done to minimize the dependence of dispersion index on quadrat positioning, which could potentially render the same pattern clumped or uniform. The variance and mean of all samplings were pooled to evaluate the standardized dispersion index and dispersion anisotropy. Statistical stationarity of images was assumed during multiple samplings of the same image. The dispersion evaluation algorithm was implemented using FORTRAN 90, and critical values of χ2 distribution were evaluated using IMSL routines. Images of webs were taken using digital cameras with field of view at least 5 cm x 5 cm. Nonwoven webs were imaged under reflected white light with a resolution of 84 pixels/cm. Colored images were converted to gray-scale using digital color separation that kept the channels having maximum amount of intensity information (evaluated using information entropy).Histogram equalization (flattening) was done to remove any illumination intensity variation within and between images. Removal of illumination variation (lighting instability) via histogram flattening improves the repeatability of data. In all images, lighter regions represented denser regions of webs. Dispersion evaluation was then performed on the preprocessed images.

    Uniformity evaluation was performed on four simulated patterns and four nonwoven webs. Figure 5 shows a simulated 30 gsm, 4.1 denier, continuous fiber web, while Figure 6 shows a simulated 20 gsm, 10.5 denier, staple fiber web. Both simulated images had a resolution of 500 pixels/cm. Of the four nonwoven webs tested, there were two spunbond (15 gsm and 60 gsm), one carded-thermobond (31 gsm), and one spunlace (58 gsm) nonwoven.

Our Web site is packed with information on our product lines. We invite you to explore the site and download the technical documentation, news items, photos, description of sample installations, system simulations and recognition demos. 

Our product line includes   

License Plate Recognition

License Plate Recognition for a wide range of applications including Parking, Access Control, Logging all vehicles & alarm when Wanted Vehicles detected.   


Facial Identification & Verification Solutions

Complete solutions, software only, SDK or rentals!

             IMAGE ANALYSIS Solutions


How we test:


Digital camcorders have brought high-quality video capture to the masses, but not all models are equal. If you're looking to buy a video camera, you know there are a lot of specs listed on the box. Unfortunately, they won't tell you what you really need to know, which is how good the footage of your daughter's birthday party, your brother's wedding, or your first independent short is going to look. There's only one way to find out, and that's to shoot a lot of footage under a variety of conditions and take a careful look at the results. We test camcorders in our camera lab under controlled lighting conditions so that we have a solid basis for comparing different models. Under indoor-color-balanced tungsten lighting, we shoot sample footage of our carefully created scene, which contains a diversity of colors, contrast, textures, and patterns. Under daylight-color-balanced HMI lighting, we shoot a series of test targets to determine how well a camcorder deals with important image-quality challenges such as noise, accurate color reproduction, and sharpness. Then we take the camcorders out in the field to see how they'll perform in typical shooting conditions.

Image-quality tests

Noise test

The laws of physics dictate that it is impossible to digitally capture an image that is completely free of noise. Although, the larger the physical size of a sensor is (not the number of pixels), the less susceptible a sensor usually is to noise. Numerous other variables impact how noisy digitally captured footage can be, including a camcorder's optics and integrated post-processing capabilities.

To evaluate the amount of noise generated by a camcorder, we start by capturing footage of an X-Rite Munsell ColorChecker Chart target (formally known as the GretagMacbeth ColorChecker Chart) using daylight-balanced HMI lighting. The camcorder's white-balance setting is set to either daylight or automatic, depending on which one is more color-accurate. Then we extract still frames, and analyze the images using Imatest image-analysis software to measurably evaluate the generated quantity of color and luminance noise. The footage is captured at the lowest-available compression setting, and at the camera's highest native resolution.

Color reproduction ability test

While color can be corrected via software after video is captured by a camcorder and copied over to a computer, it's usually best to start with captured footage that is as color-accurate as possible--especially for those instances when the footage will not be edited or might be burned directly to disc.

To evaluate how well a camcorder can reproduce accurate colors, we capture footage of the X-Rite Munsell ColorChecker Chart target using daylight-balanced HMI lighting. Footage is captured at the camcorder's daylight white-balance setting. We then extract still frames and analyze the images using the Imatest image-analysis software in order to measurably evaluate a camcorder's ability to reproduce colors correctly. The footage is captured at the lowest-available compression setting and at the camera's highest native resolution.

Sharpness test

The potential sharpness of an image is directly impacted by the resolution of the sensor that captured the image. However, several other variables impact the overall sharpness of a digitally captured image, especially the quality of a camcorder's optics and its integrated postprocessing capabilities.

To evaluate how well a camcorder can create sharp images, we capture footage of an ISO 12233 test target using daylight-balanced HMI lighting, with the camcorder set to automatic white balance. We then extract still frames and analyze the images using the Imatest image-analysis software to measurably evaluate a camera's capability when capturing sharp details. The footage is captured at the lowest-available compression setting, and at the camera's highest native resolution.

Tungsten lighting tests

In our camera lab, we shoot a fixed scene made up of objects with a wide range of colors, textures, and reflective properties. The video is shot under color-balanced (centered around 3,200K), tungsten studio lights. We use the camcorder's automatic exposure and set the focal length of the lens to a point in the middle of the zoom range for these tests. We set the camcorder to its highest-available quality setting, and test with three different white-balance settings:

  • Automatic white balance
  • Manual white balance
  • White balance preset for tungsten or indoor lighting

We also test a camcorder's low-light capability by shooting the scene lit by only a shaded lamp with a 150-watt incandescent bulb. We use the automatic white-balance setting during this part of the test and cycle through all special low-light modes available on the camera.

In addition to the video created in our camera lab, we shoot video in both indoor and outdoor settings. We shoot various scenes in a variety of lighting situations, capturing footage that contains a diversity of colors, contrast, patterns, and light levels. We also shoot video that includes people with a variety of skin tones in order to evaluate how well a camcorder captures them.

We evaluate the quality of the video for sharpness, detail, proper exposure, accurate color reproduction and saturation, white-balance accuracy, dynamic range, and tonal separation. We also look for typical problems that arise with camcorder footage, including image noise, artifacts, and lens distortion. All of the footage is reviewed on a professional video monitor.

If the camcorder offers still-image capture to a flash memory card, we follow our standard procedures for testing digital still cameras and capture photos for evaluation in addition to the video.

Image-quality characteristics

Here are some examples of the image-quality characteristics we consider when evaluating a camcorder.

White balance

The sample at the top left has correct white balance; the whites and grays look neutral, and there's no discernible color cast. We consider the sample on the bottom left acceptable. Even though the image appears a bit too cool (bluish) and measurements indicate that the blue channel is a bit too strong, it still lacks an obvious color cast. The incorrect sample on the top right has an obvious, distracting color cast.


The top left and right samples are overexposed and underexposed, respectively. Using the correct exposure on the bottom left as a reference, you can see that in the overexposed sample, the sky looks blown out, and you can't tell that there's a glass wall on the right side because it loses the reflection. The underexposed version loses detail and definition in the white pipes.

Color saturation

The sample to the immediate left most accurately represents our test scene. The sample on the top left has undersaturated colors; it looks as if there is a smoky filter in front of the scene. The sample on the top right is oversaturated, with colors that look too vivid to be real.

Dynamic range

We use various techniques to evaluate dynamic range, but these are two quick indicators: to judge quality of shadows, you should be able to clearly see the gorilla's face and the various shades of brown that comprise it. For good highlights, you should see well-defined reflections off the CD and the detail of the hat's weave.


The top left and right examples respectively show low and high noise, and the sample to the immediate left displays moderate noise. The noise in these samples appears as white spots. We consider the quality of the first sample to be good, the second unusable, and the third acceptable.

Testing equipment



CALL Barry on +27 31 764 3077  or   + 27 (0) 82-562-8225  or E-Mail NOW (info at I-Cube dot co dot za)  OR Fax Number : 0866539659 OR Contact one of our DISTRIBUTORS or an independent security advisor!

I-CUBE and PlanetCCTV announce a partnership whereby the I-CUBE Facial and LPR products will now be shipped PRE-installed on all PlanIT CCTV products 

Please download (ZIP / Word) the I-Cube Company Profile and Products if you require more information

I-Cube.   All rights reserved.  Revised: February 18, 2008 .                                  BTD (QG) Quotes