Spectral Imaging is the detection of light reflected by the sample with the use of specialized sensors. It is measured in spectral bands. The higher the number of bands, the higher is the accuracy, flexibility and information content.
Hyperspectral Imaging uses an imaging spectrometer to collect spectral information. This device is called a hyperspectral camera which measures hundreds of spectra at each pixel, unlike single-point spectroscopy. The collected spectra are used to form a 3-D image of the target food called a hyperspectral cube. By analyzing this 3-D image, real-time insights can be gathered on 'what is in my food, how much and where?'.
How Hyperspectral imaging is changing the food industry?
Food can be homogeneous or heterogeneous in nature. To understand the chemical composition of food is complex and the food industry relies on time-consuming primary methods. Successful application of hyperspectral imaging in food quality system is primarily due to the capability of spectral-imaging technology to detect internal defects, quantify chemical makeup of food and detect micro-contaminants in both heterogeneous and homogeneous food samples. It is of paramount importance to understand the competitive advantage of hyperspectral imaging as it eliminates any tedious sample preparation steps such as grinding or weighing samples before analysis.Once the food sample is scanned through hyperspectral cameras, we rely on the predictive capabilities of our AI software to gather real-time insights on the food. In the context of machine learning and imaging technology, we gather a few food samples to give the brain to our software to look for different targets in the food. It can detect ob...