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