MIFT: A Mirror Reflection Invariant Feature Descriptor
نویسندگان
چکیده
In this paper, we present a mirror reflection invariant descriptor which is inspired from SIFT. While preserving tolerance to scale, rotation and even affine transformation, the proposed descriptor, MIFT, is also invariant to mirror reflection. We analyze the structure of MIFT and show how MIFT outperforms SIFT in the context of mirror reflection while performs as well as SIFT when there is no mirror reflection. The performance evaluation is demonstrated on natural images such as reflection on the water, non-rigid symmetric objects viewed from different sides, and reflection in the mirror. Based on MIFT, applications to image search and symmetry axis detection for planar symmetric objects are also shown.
منابع مشابه
MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching
The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these ...
متن کاملDPML-Risk: An Efficient Algorithm for Image Registration
Targets and objects registration and tracking in a sequence of images play an important role in various areas. One of the methods in image registration is feature-based algorithm which is accomplished in two steps. The first step includes finding features of sensed and reference images. In this step, a scale space is used to reduce the sensitivity of detected features to the scale changes. Afterw...
متن کاملAn improvement to the SIFT descriptor for image representation and matching
0167-8655/$ see front matter 2013 Elsevier B.V. A http://dx.doi.org/10.1016/j.patrec.2013.03.021 ⇑ Corresponding author. Tel./fax: +86 29 82667836 E-mail addresses: [email protected], liugz@xjtu Constructing proper descriptors for interest points in images is a critical aspect for local features related tasks in computer vision and pattern recognition. Although the SIFT descriptor has been p...
متن کاملπ-SIFT: A Photometric and Scale Invariant Feature Transform
For many years, various local descriptors that are insensitive to geometric changes such as viewpoint, rotation, and scale changes, have been attracting attention due to their promising performance. However, most existing local descriptors including the SIFT (Scale Invariant Feature Transform) are based on luminance information rather than color information thereby resulting in instability to p...
متن کاملFWLBP: A Scale Invariant Descriptor for Texture Classification
In this paper we propose a novel texture recognition feature called Fractal Weighted Local Binary Pattern (FWLBP). It has been observed that fractal dimension (FD) measure is relatively invariant to scale-changes, and presents a good correlation with human perception of surface roughness. We have utilized this property to construct a scale-invariant descriptor. We have sampled the input image u...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009