An Efficient and Precise Remote Sensing Optical Image Matching Technique Using Binary-Based Feature Points

Matching local feature points is an important but crucial step for various optical image processing applications, such as image registration, image mosaicking, and structure-from-motion (SfM). Three significant issues associated with this subject have been the focus for years, including the robustness of the image features detected, the number of matches obtained, and the efficiency of the data processing. This paper proposes a systematic algorithm that incorporates the synthetic-colored enhanced accelerated binary robust invariant scalar keypoints (SC-EABRISK) method and the affine transformation with bounding box (ATBB) procedure to address these three issues. The SC-EABRISK approach selects the most representative feature points from an image and rearranges their descriptors by adding color information for more precise image matching. The ATBB procedure, meanwhile, is an outreach that implements geometric mapping to retrieve more matches from the feature points ignored during SC-EABRISK processing. The experimental results obtained using benchmark imagery datasets, close-range photos (CRPs), and aerial and satellite images indicate that the developed algorithm can perform up to 20 times faster than the previous EABRISK method, achieve thousands of matches, and improve the matching precision by more than 90%. Consequently, SC-EABRISK with the ATBB algorithm can address image matching efficiently and precisely.

Inversion-free geometric mapping construction: A survey

A geometric mapping establishes a correspondence between two domains. Since no real object has zero or negative volume, such a mapping is required to be inversion-free. Computing inversion-free mappings is a fundamental task in numerous computer graphics and geometric processing applications, such as deformation, texture mapping, mesh generation, and others. This task is usually formulated as a non-convex, nonlinear, constrained optimization problem. Various methods have been developed to solve this optimization problem. As well as being inversion-free, different applications have various further requirements. We expand the discussion in two directions to (i) problems imposing specific constraints and (ii) combinatorial problems. This report provides a systematic overview of inversion-free mapping construction, a detailed discussion of the construction methods, including their strengths and weaknesses, and a description of open problems in this research field.

Matching Detection of Crane Hook and Ladle Lug before Ladle Hoisting

Reliable matching between the crane hook and ladle lug is a key requirement for the safe hoisting of a ladle in steelmaking. A novel method is proposed to detect the matching between the hook and lug using surface acoustic wave radio frequency identification (SAW RFID) localization. SAW RFID tags are attached to the surface of the lug and the hook. The position of the lug is estimated via a geometric mapping approach with a special position of the tag and the reader’s antenna, and the position of the hook is estimated by a synthetic aperture approach with the hook’s movement pattern. Afterwards, the matching judgement is determined based on the relative position between the hook and lug. The proposed method employs only two SAW tags and two reader antennas, facilitating installation and routine maintenance. Numerical simulation and physical experiments demonstrate that the proposed method works effectively for matching detection.

Modified Gabor Wavelet Transform in Prediction of Cancerous Genes

Cancer is the leading cause of mortality all over the world which in general is the result of some kind of mutation in the genetic sequence. With recent advancements in Digital Signal Processing(DSP) techniques, it has become possible to classify cancerous gene sequences without carrying out extensive biological experiments. In this paper, the Geometric mapping technique along with Modified Gabor wavelet transform (MGWT) has been incorporated to segregate cancerous and non-cancerous gene sequences. This Gabor wavelet based transform technique used in the present research work benefits from the fact that it is independent of the window length which in conjunction with Geometric mapping is used to obtain the spectral components present in the signal accurately and with reduced complexity. This technique has been applied on numerous benchmark datasets and the results obtained prove the performance of the proposed method.