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Image retrieval based on the directional edge similarity

机译:基于方向边缘相似度的图像检索

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Abstract: This paper introduces a new shape based image retrieval scheme. This scheme employs the image edge directional similarity in generating the feature vector. The previous comparable schemes consider the point edge angles without any regard for its neighboring point edges. Those schemes offer some advantages such as translation, scaling and rotation invariant. Their problems are high sensitivity to false edges or high computational barrier, and lack of considering spatial domain correlation in feature vector components. This new scheme has all the advantages of previous scheme, because it employs the edges point angles, but overcomes their drawbacks with considering the point edge directional similarity. This scheme uses two factors in producing the feature vector which improves the retrieval effectivity; the edge point angle and amplitude, and its relation with its neighboring edge points. This scheme is robust against noise, since noise has little effect on similar directional edges, consequently there is no need to do any extra computation to identify the false edges. This results in low computational cost of this scheme in comparison with other similar schemes. !11
机译:摘要:本文介绍了一种新的基于形状的图像检索方案。该方案在生成特征向量时采用图像边缘方向相似性。先前的可比较方案在不考虑其相邻点边缘的情况下考虑了点边缘角度。这些方案提供了一些优势,例如平移,缩放和旋转不变。他们的问题是对虚假边缘的敏感度高或计算壁垒高,并且缺乏考虑特征向量分量中的空间域相关性。该新方案具有先前方案的所有优点,因为它采用了边缘点角,但是在考虑了点边缘方向相似性的情况下克服了它们的缺点。该方案在生成特征向量时使用了两个因素,从而提高了检索效率。边缘点的角度和幅度,及其与相邻边缘点的关系。由于噪声对相似方向的边缘影响很小,因此该方案具有较强的抗噪声能力,因此无需进行任何额外的计算即可识别出虚假边缘。与其他类似方案相比,这导致该方案的计算成本低。 !11

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