Template matching for inventory management using fuzzy color histogram and spatial filters

Automated counting of objects is useful for firms to keep a track of the number of objects present in the inventory. This in turn helps them to adjust their production rate accordingly and thus efficiently cater to the market demand of goods. In this paper, we have proposed a methodology for object counting using color histogram based segmentation and spatial filters. Given a prototype image, which refers to the object's image one wishes to count, the scene image is first segmented using color histogram to extract out the most likely location of the prototype. This is followed by the calculation of sum of squared distances and use of spatial filters to reject false alarms. To improve the system's robustness towards uneven lighting conditions, a fuzzy based color histogram has also been introduced. The paper then further compares the two histogram methods for their performance and computational complexity. The complete algorithm has been developed into a desktop application which uses a remotely connected camera to give real time object count. The methodology and application were tested by performing real time experiments. Both of them have shown good results under normal illumination conditions.