Detecting 3D objects from monocular RGB images is an ill-posed task for lacking depth knowledge, and monocular-based 3D detection methods perform poorly compared with LiDAR-based 3D detection methods. Some bird’s-eye-view-based monocular 3D ...

The objective of image contrast enhancement is to improve the contrast level of images, which are degraded during image acquisition. Image contrast enhancement is considered as an optimization problem in this paper and the artificial bee colony (ABC) ...

In this paper, a novel visual cryptography VC copyright protection scheme based on artificial bee colony algorithm ABCA is proposed. First, we apply wavelet decomposition discrete wavelet transform, DWT to decompose the cover image, and ABCA is used to ...

Using the reflectance component of images directly as the output of Retinex enhancement lacks adjustability and removing illuminance completely from the non-uniform image leads to the lack of coordination between gray scales and the visual effects is ...

Clustering is concerned with partitioning a dataset into homogeneous groups. One of the most popular clustering methods is k-means clustering because of its simplicity and computational efficiency. K-means clustering involves search and optimisation. ...

Image threshold segmentation based on artificial bee colony algorithm (ABCA) and maximum entropy is presented in this paper. The entropy function is simplified with several parameters. The ABC is applied to search the maximum value of entropy function. ...

► We propose a new wavelet-based image interpolation approach. ► We propose a three-component exponential mixture model to formulate both magnitude and sign of wavelet coefficients. ► We exploit the ant colony ...

Wavelet-based image interpolation typically treats the input image as the low frequency subbands of an unknown wavelet-transformed high-resolution image, and then produces the unknown high-resolution image by estimating the wavelet ...

Image denoising is an important task in image analysis. To improve the performance of high-density salt and pepper noise denoising, a novel approach is proposed in this paper. This approach includes two steps. In the first step, the noise pixels are ...

Ant colony optimization (ACO) is an optimization algorithm inspired by the natural collective behavior of ant species. The ACO technique is exploited in this paper to develop a novel image edge detection approach. The proposed approach is able to ...

Wavelet shrinkage is an image denoising technique based on the concept of thresholding the wavelet coefficients. The key challenge of wavelet shrinkage is to find an appropriate threshold value, which is typically controlled by the signal variance. To ...

This paper proposes an adaptive unsupervised scheme that could find diverse applications in pattern recognition as well as in computer vision, particularly in color image segmentation. The algorithm, named Ant Colony-Fuzzy C-means Hybrid Algorithm (AFHA)...

In this paper, we proposed an improved image binary segmentation based Ant Colony Algorithm. Within different image areas, different iteration numbers and steps have been set for ants, achieving superior image segmentation results. Experimental results ...

Ant Colony Optimization (ACO) is a newly proposed intelligent algorithm for solving discrete optimization problems such as the Travelling Salesman Problem (TSP). In this paper we introduce a novel ACO-based clustering algorithm and exploit its ...

The aim of image enhancement over distributed video sensor network (DVSN) is to fuse multiple images acquired by a set of video sensors to produce a single image with more visual information. For that, a wavelet-domain Bayesian approach is proposed in ...

Wavelet-based image interpolation typically treats the input image as the low-pass filtered subbands of an unknown wavelet-transformed high-resolution image, and then produces the unknown high-resolution image by estimating the wavelet coefficients of ...