A robust feature-based registration method of multimodal image using phase congruency and coherent point drift
نویسندگان
چکیده
This paper presents a new feature matching algorithm for nonrigid multimodal image registration. The proposed algorithm first constructs phase congruency representations (PCR) of images to be registered. Then scale invariant feature transform (SIFT) method is applied to capture significant feature points from PCR. Subsequently, the putative matching is obtained by the nearest neighbour matching in the SIFT descriptor space. The SIFT descriptor is then integrated into Coherent Point Drift (CPD) method so that the appropriate matching of two point sets is solved by combining appearance with distance properties between putative match candidates. Finally, the transformation estimated by matching the point sets is applied to registration of original images. The results show that the proposed algorithm increases the correct rate of matching and is well suited for multi-modal image registration.
منابع مشابه
DPML-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 کاملFeature based RDWT watermarking for multimodal biometric system
This paper presents a 3-level RDWT biometric watermarking algorithm to embed the voice biometric MFC coefficients in a color face image of the same individual for increased robustness, security and accuracy. Phase congruency model is used to compute the embedding locations which preserves the facial features from being watermarked and ensures that the face recognition accuracy is not compromise...
متن کاملContourlet-Based Edge Extraction for Image Registration
Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transform modeling, and finally image resampling. As the accuracy of a registration process is highly dependent to the fe...
متن کاملDisguised Face Recognition by Using Local Phase Quantization and Singular Value Decomposition
Disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is presented which deals with two main challenges. The first challenge is when an individual intentionally alters the appearance ...
متن کاملFast phase-based registration of multimodal image data
An interesting problem in pattern recognition is that of image registration, which plays an important role in many vision-based recognition and motion analysis applications. Of particular interest among registration problems are multimodal registration problems, where the images exist in different feature spaces. State-of-the-art phased-based approaches to multimodal image registration methods ...
متن کامل