Jayati Ghosh Dastidar

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It is at times important to detect human presence automatically in secure environments. This needs a shape recognition algorithm that is robust, fast and has low error rates. The algorithm needs to process camera images quickly to detect any human in the range of vision, and generate alerts, especially if the object under scrutiny is moving in certain(More)
Sometimes a simple and fast algorithm is required to detect human presence and movement with a low error rate in a controlled environment for security purposes. Here a light weight algorithm has been presented that generates alert on detection of human presence and its movement towards a certain direction. The algorithm uses fixed angle CCTV camera images(More)
The cost of a database query can be optimized so that a more efficient query can be generated. However not many tools are available which work independently to optimize the cost of a query. This article is based on a tool that we developed to serve the purpose. It uses an Oracle Database and Linear Programming Problem concepts to evaluate the optimum cost(More)
Detection of an object and tracking its movement is a challenging problem in the field of computer vision and image processing. In this paper an efficient scheme has been proposed to detect intrusion in a security-critical environment and to track the movement of the intrusion by automatically shifting the focus of a CCTV camera by rotating it using a motor(More)
In this paper we have presented a hand gesture recognition library. Various functions include detecting cluster count, cluster orientation, finger pointing direction, etc. To use these functions first the input image needs to be processed into a logical array for which a function has been developed. The library has been developed keeping flexibility in mind(More)
This paper presents a method to differentiate the foreground objects from the background of a color image. Firstly a color image of any size is input for processing. The algorithm converts it to a grayscale image. Next we apply canny edge detector to find the boundary of the foreground object. We concentrate to find the maximum distance between each(More)
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