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Image Recognition Method Using Intensity Gradient Vectors

机译:强度梯度向量的图像识别方法

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This paper proposes a method for general image recognition based on the progress of increasing the pixels of image sensors and improving image quality. This method can also adapt to images which have undergone geometric transformations such as the rotation and movement of images. The proposed method uses a voting system that utilizes vectors. This method uses vectors which represent intensity gradients and vectors which show position to express images and also defines voting vectors and similarity for the recognition. In addition, the proposed method has characteristics of concentrating voting locations at an origin point if there are identical images such that the voting results do not influence geometric transformations. When we performed experiments on natural images including original images which may have undergone image processing such as Gaussian or median filtering and JPEG compression, we understood that distinct differences appeared in the similarities and that recognition was possible even if an artificial process was added to the images. Even further, when we examined recognition of images using the greatest number of voting points as an application of this method, we were able to show that the recognition capability was high and that a partial image contained in one image could also be recognized.
机译:提出了一种基于图像传感器像素增加和图像质量提高的一般图像识别方法。该方法还可以适应经历了诸如图像的旋转和运动的几何变换的图像。所提出的方法使用利用矢量的投票系统。该方法使用代表强度梯度的矢量和显示位置的矢量来表示图像,并且还定义了投票矢量和相似性以进行识别。另外,如果存在相同的图像,则所提出的方法具有将投票位置集中在原点的特征,使得投票结果不会影响几何变换。当我们对包括可能经过图像处理(例如高斯或中值滤波和JPEG压缩)的原始图像进行自然图像实验时,我们了解到相似之处出现了明显的差异,即使对图像进行了人工处理,也可以进行识别。更进一步,当我们使用最大数量的投票点检查图像的识别作为此方法的应用时,我们能够证明识别能力很高,并且一张图像中包含的部分图像也可以被识别。

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