Shape recognition of object is important research direction in pattern recognition, and is widely used in image analysis, machine vision and target discrimination.
物体的形状识别是模式识别的重要方向，广泛应用于图像分析、机器视觉和目标识别等领域。
Shape is the inherence characteristic of an object in the image, and it is the important character used for the object recognition.
形状是图像中目标的基本内在特性，是用于目标识别的重要特征，因此基于形状的目标识别方法研究具有重要意义。
To solve the problem of ellipse - object - shape parameters detection in noise image, a new detection algorithm using nonlinear data fitting model and cross-reference iterative method is proposed.
为提高噪声环境下椭圆类物体形状检测算法的稳定性与准确性，本文提出非线性数据拟合模型结合交叉参考迭代的新思路。
Figure image edge detection is very important basis in image -division, identify object zone, pick-up zone shape.
数字图像的边缘检测是图像分割、目标区域识别、区域形状提取等图像分析领域中十分重要的基础。
The reconstruction for the lost image information of the arbitrary-shape area is very important for the disocclusion and restoration of the image and the object detection in the infrared image.
任意形状区域丢失图像信息的重建对于图像中遮挡区域的去除、受损图像的复原和红外图像中的目标检测具有十分重要的意义。
Shape feature is the most suitable tool in characterizing image content object which has clear object outline.
形状特征是对图像中边界清晰的目标的最好表达方式。
Shape recognition of object is one of the important directions in pattern recognition, and is widely used in image analysis, machine vision and target discrimination, etc.
物体的形状识别是模式识别的重要方向之一，广泛应用于图像分析、机器视觉和目标识别等领域。
Fringe examination of the digital image is an important fundamental to explore the further image processing areas, such as image division, object region reorganization and region shape picking-up.
数字图像的边缘检测是图像分割、目标区域的识别、区域形状提取等图像分析领域十分重要的基础。
The shape descriptor developed in this thesis has the aim to represent the object boundaries computationally and reliably, and to describe the image semantically.
本文中的形状描绘子用于对物体边界进行可靠的计算机表述，进而对图像进行语义层面的描述。
Corners are important local features of an image, and are the feature points that can be fully describe the shape of the object.
角点是图像的一种重要的局部特征，是能充分描述物体形状的特征点。
This paper presents a method which can be used for the shape analysis of two-dimensional image of a moving object in terms of the fast transformation (r transformation).
本文提出了将一种快速变换(r变换)用于对运动目标的二维图象进行形状分析的方法。
Based on the image processing, object shape features were automatically measured and achieve to object of system. The results show that these methods are very effective.
在图像处理的基础上，系统自动测量出指定目标的形状参数，实现了系统的测量要求。
A method based on local HSV image and shape of object to recognize object is proposed for robot tracking.
采用基于局部图像的HSV阈值分割和基于形状提取相结合的方法识别物体。
When the object underwater reflects the sound wave, we can clearly see its shape in the form of a 3-dimensional image.
当水下物体反射声波时，我们可以清楚地看到它的三维图像。
Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps.
首先在画素级上提取影像的纹理和形状结构特征，在构建的多尺度分割集影像上提取物件的区域光谱特征。
The color of certain object surface has a constant feature, irrelevant to the object surface shape. But the color of the image is variablebecause of the existence of highlights.
某种材料表面的颜色具有与形状无关的稳定特性，但图象中表面的颜色由于存在高光和影调而是变化的。
To appropriately evaluate a surface shape of an object to be inspected regardless of the relative positions of a light source and an image-taking device with respect to the object.
本发明能够与光源和拍摄装置对于检查对象物的相对位置无关地适当地评价对象物的表面形状。
To appropriately evaluate a surface shape of an object to be inspected regardless of the relative positions of a light source and an image-taking device with respect to the object.
本发明能够与光源和拍摄装置对于检查对象物的相对位置无关地适当地评价对象物的表面形状。
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