Image segmentation method based on multi-spectral image fusion and morphology reconstruction

The color values of some mature fruits are the approximations with those of their branches and leaves. The gray values of fruit and leaf have only the small difference. The fruit target cannot be extracted precisely, from the leaf background using the single spectral image. A novel image segmentation method was proposed based on multi-spectral image fusion and morphology reconstruction. First, some fusion methods were applied to the multi-spectral image, such as the principal component analysis (PCA) fusion, the wavelet transformation fusion as well as arithmetic combination (NIR/H) fusion of the visual and the near-infrared images of the same target; then, segmentation algorithm based on the morphology reconstruction was applied to the fusion image. Through the experiment from many apple and tomato images, the results indicate that the morphology reconstruction segmentation based on multi-spectral image fusion, gives better segmentation results. In particular, the effect of morphology reconstruction segmentation using watershed transformation based on wavelet transformation fusion, is the best with good self-adaptability.