Grass Field Detection for TV Picture Quality Enhancement
Current TV image enhancement can be improved if the image is analyzed, objects of interest are segmented, and each segment is processed with content-specific enhancement algorithms. In this paper we present an algorithm for segmenting grass areas in video sequences. The system employs multi-scale texture analysis and adaptive color and position models for computing a pixel-based soft segmentation map. Compared to previously reported algorithms, our system shows a clear improvement in the detection result: at 10% false positive rate, the true positive rate of our algorithm yields 91%, vs. 66% and 58% of two existing methods.