An Improved Computational Approach for Salient Region Detection

Abstract

<span style="font-size: 10pt; font-family: "Times New Roman"; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">Salient region detection in images is very useful </span><span style="font-size: 10pt; font-family: "Times New Roman"; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">for image processing applications like image compressing, image segmentation, object detection and recognition. In this paper, an improved approach to detect salient region is presented</span><span style="font-size: 10pt; font-family: "Times New Roman"; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">. </span><span style="font-size: 10pt; font-family: "Times New Roman"; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">The proposed method can generate a robust saliency map and extract salient regions with precise boundaries. In the proposed method, local saliency, global saliency and rarity saliency of three kinds of low-level feature contrast of intensity, color and orientation are used to compute the visual saliency. A new feature integration strategy is proposed in this paper. This method can select features and compute the weights of the features dynamically by analyzing the effect of different features on the saliency. Then a more robust saliency map is obtained. It has been tested on many images to evaluate the validity and effectiveness of the proposed method. We also compare our method with other salient region detection methods and our method outperforms other methods in detection results.</span><span style="font-size: 10pt; font-family: "Times New Roman"; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-bidi-font-size: 9.0pt;" lang="EN-US"> </span&gt

Weld seam profile detection and feature point extraction for multi-pass route planning based on visual attention model

“…The goal in this metric is to increase saliency of the laser stripe because of its long length. Zhang et al [29] presented three metric methods using primitive orientation and intensity feature maps for object detection from natural pictures, and these methods did not work well when they were used for detecting the weld seam profile. In fact, the dimension metric is composed of two steps: first applying threshold segmentation, and then carrying out a clustering algorithm based on the nearest neighbor.…”

A hierarchical computational model of visual attention using multi-layer analysis

“…H (hue) channel and S (saturation) channel are used to describe the color feature of the image. The method to compute the saliency has been proposed in our other paper [9] in detail. Here we just describe the main idea of the method in brief.…”

A Multitarget Visual Attention Based Algorithm on Crack Detection of Industrial Explosives

“…Visual attention based algorithm reveals the mechanisms of biological visual intelligence [15][16][17][18][19]. It has wide applications in various locations as reported by some computer vision researchers [20][21][22][23][24][25][26].…”