• In this method, the SVM classification model combined with texture analysis is established on the basis of texture extraction from SPOT5 remote sensing image.

    该方法在对SPOT5遥感影像进行纹理特征提取的基础上,构建了结合多窗口纹理的SVM模型。

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  • The contents in the paper include acoustic image preprocessing, feature extraction of texture and shape, and classifier design.

    内容涉及声图像的预处理、纹理和形状特征的提取,以及分类器的设计等。

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  • Feature extraction based on the histogram, texture, projection and shape of the defect images was also investigated.

    研究了基于缺陷图像直方图、纹理、投影和形状的特征提取。

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  • The techniques for realization of OWT and applications in image feature extraction and texture segmentation are explored thoroughly.

    深入研究了光学子波变换的实现技术及其在图象特征提取和纹理图象分割等方面的应用。

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  • This paper presents a new license plate extraction method based on fuzzy set by employing color characteristics and texture characteristics of the license plate.

    利用了车牌的颜色特征与纹理特征,提出一种新的基于模糊集的车牌提取方法。

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  • The description and extraction of SAR image texture feature is important to texture segmentation.

    SAR图像纹理特征的描述和提取是纹理分割的关键。

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  • Accordingly, we propose an improved feature extraction scheme, adopting the tone of filtered image combined with the texture features based on the GLCM of unfiltered image to form the feature vector.

    针对这种情况,提出了一种改进的特征提取方法,将基于原图像的灰度级共生矩阵提取的纹理特征与滤波后图像的灰度特征进行组合用于分类。

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  • The extraction of forest texture feature from color forest aerial remote sensing images is an important part of the automatic interpretation of forest types achieved by computer.

    彩色森林航空遥感图像中森林纹理特征提取是实现计算机自动判读的重要环节。

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  • This paper proposes a method for objects extraction based on high and color texture features.

    提出一种基于高度和彩色纹理信息的目标识别方法,其目的是提取具有相对高度的地物。

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  • A new texture feature extraction method using Local Walsh Transform (LWT) is presented. The definition of LWT is given. The statistical properties of LWT coefficients are analyzed.

    介绍了一种利用局部沃尔什变换(LWT)提取图像纹理特征的新方法,给出lwt的定义,并分析了LWT系数的统计特性及其各阶矩的纹理鉴别性能。

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  • Finally, based on the work of above, proposed a method of description and extraction image color and texture features in the dual tree complex wavelet transformation domain.

    最后,在上面工作的基础上,提出了基于对偶数复小波域的图像的颜色和纹理特征的描述和提取方法。

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  • This thesis proposes a vehicle detection proposal based on the extraction of shadow with a combination of vehicles' texture and symmetry of gray-scale.

    论文提出了基于阴影提取、车辆纹理与灰度对称性相结合的车辆检测方案。

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  • We do some researches on the algorithm of CBIR, and pay more attention on the global feature (including color, edge and texture feature) extraction and matching algorithms.

    对基于内容的图象信息检索算法作了研究。重点阐述了对颜色、边缘、纹理等全局特征的提取与匹配算法。

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  • Similarly, the work of texture feature extraction is obtained by using co-occurrence matrix or frequency analysis based on wavelet transform depending on different characteristics of images.

    在纹理特征提取方面,针对不同纹理特点分别采用了基于共生矩阵的统计纹理分析和基于小波变换的频谱纹理分析两种方法予以实现。

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  • Likewise, granular computing theory is trying to apply to texture features extraction and accurate segmentation of chest HRCT image.

    同样,粒计算理论也在被尝试应用于HRCT图像纹理特征值提取和肺部组织分割。

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  • A nature scene image color-texture feature extraction method based on human visual system (HVS) was proposed.

    提出了基于人类视觉系统的自然场景图像颜色和纹理特征提取方法。

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  • This paper proposes a fast algorithm for texture feature extraction. The new algorithm is suitable for remote image classification on line.

    给出一种抽取纹理特征的算法,该算法实时性强,适于在线遥感图像分类。

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  • Among the contend-based retrieval technologies, feature extraction is most important. For instance, color, texture and shape feature etc.

    基于内容检索技术中必不可少的关键步骤就是图像特征的提取,其中可提取的特征有颜色、纹理和形状等。

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  • Then, land cover classification and residential areas extraction with combined texture feature was proposed by the sufficient analysis of the texture feature with different image window.

    然后在充分分析影像不同窗口纹理特征的基础上,提出应用组合纹理特征进行土地覆盖分类和居民地信息提取方法。

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  • The excellent characteristics of rotation-invariance, good orientation selection and finite redundancy are fully utilized, and applied in texture feature extraction.

    充分利用双树复小波变换的旋转不变性、良好的方向选择性以及有限的冗余等优点,将其有效地应用于纹理特征提取过程中。

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  • This paper discusses the optimization of back propagaton neural networks for the grain texture feature, extraction in grain classification.

    主要讨论了在谷物纹理识别中对神经网络的优化。

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  • The approach effectively reduces the influence of peripheral background intensities texture on the extraction of a cell region.

    提出的方法结合了前人方法的优点,能有效降低周围背景灰度和细胞区域纹理对对分割结果的影响。

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  • A change detection method regarding shadow and projection difference is designed by integrating texture feature differences, automatic shadow extraction and projection difference handling.

    利用阴影差值图像消除纹理差值法变化检测结果中的阴影影响,取得了很好的实验效果。

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  • A change detection method regarding shadow and projection difference is designed by integrating texture feature differences, automatic shadow extraction and projection difference handling.

    利用阴影差值图像消除纹理差值法变化检测结果中的阴影影响,取得了很好的实验效果。

    youdao

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