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This article focuses on an efficient algorithm for measuring object displacement and velocity from real time video. The proposed technique for object identification and tracking is based on background subtraction with optimized threshold binarization. Mapping techniques have been developed to relate image with real world. The algorithm is also capable of working with a bad lighting conditions using histogram equalization approach. Further, the real scenarios like presence of noise, shadow, and multiple moving object environments have been taken under consideration for developing the algorithm.

The goal of this article is to design an effective scheme for extraction of Bangla/Devnagari text from outdoor images. We first segment a color image using fuzzy c-means algorithm. In Bangla/Devnagari script, text may be attached/unattached to the headlines. Hence, after segmentation, headlines are detected from each connected components using morphology. Now, the components attached or close to the detected headlines are separated. Further by applying certain shape and position based purification we could distinguish text and non text. Our experiments on a dataset of 100 outdoor images containing Bangla and/or Devnagari text reveals satisfactory performance.

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