An improving noise eliminated difference template based on the analysis of object and background gray value also has been developed to eliminate the low frequency noise in image.
对图像中的低频噪声，基于对图像中目标与背景灰度值特点的分析，提出了改进的差分去噪声模板。
Due to the HT, the system is very effective in recognizing object in an image with noise, gaps and complicated background.
由于利用了HT，使得整个系统对于有噪声、目标残缺、背景复杂的目标图像具有较强的识别能力。
The method defines different member function for the object and background of the image to transform the image into fuzzy domain with maximum fuzzy entropy.
该方法将图像分为目标和背景，并分别建立相应的模糊隶属函数来描述图像各个灰度级属于目标和背景的模糊特性，进而给出图像模糊熵的描述。
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