High density QR code with multi-view scheme

[[abstract]]Since the data storage capacity per unit area of a QR code is very limited, it is restricted in various QR code applications. An approach is proposed based on visual skew to improve the data capacity of the QR code. The proposed method can enhance the capacity of the QR code per unit area by using different angle views to combine several QR codes together. The storage capacity of the proposed mechanism can be increased 1.5 times per unit area more than that of the normal QR code.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙

Conditional-Sorting Local Binary Pattern Based on Gait Energy Image for Human Identification

[[abstract]]Gait recognition systems have recently attracted much interest from biometric researchers. This work proposes a new feature extraction method for gait representation and recognition. The new method is extended from the technique of Local Binary Pattern (LBP) by changing the sorting method of LBP according to the blend direction to create a new approach, Conditional-Sorting Local Binary Pattern (CS-LBP). After synchronizing and calibrating the gait sequence images, a cycle of images from the gait sequence can be captured to form a Gait Energy Image (GEI). We then apply the CS-LBP on GEI to derive different blend direction images and calculate the recognition ability for each blend direction image for feature selections. To solve the classification problem, the Euclidean distance and Nearest Neighbor (NN) approaches are used. With the experiments carried out on the CASIA-B gait database, our proposed gait representation has a very good recognition rate.[[sponsorship]]Worldcomp[[conferencetype]]國際[[conferencedate]]20130722~20130725[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Las Vegas, US

Improved low complexity algorithm for 2-D integer lifting-based discrete wavelet transform using symmetric mask-based scheme

[[abstract]]Wavelet coding performs better than discrete cosine transform in visual processing. Moreover, it is scalable, which is important for modern video standards. The transpose memory requirement and operation speed are the two major concerns in 2-D lifting-based discrete wavelet transform (LDWT) implementation. This letter presents a novel algorithm, called 2-D symmetric mask-based discrete wavelet transform (SMDWT), to improve the critical issue of the 2-D LDWT, and then obtains the benefit of low-latency reduced complexity, and low transpose memory. The SMDWT also has the advantages of reduced complexity, regular signal coding, short critical path, reduced latency time, and independent subband coding processing. Furthermore, the 2-D LDWT performance can also be easily improved by exploiting an appropriate parallel method inherent to SMDWT. The proposed method has a significantly better lifting-based latency and complexity in 2-D DWT than normal 2-D 5/3 integer LDWT without degradation in image quality. The algorithm can be applied to real-time image/video applications.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙

A Real-Time Object Recognition System Using Adaptive Resolution Method for Humanoid Robot Vision Development

[[abstract]]The research of autonomous robots is one of the most important challenges in recent years. Among the numerous robot researches, the humanoid robot soccer competition is very popular. The robot soccer players rely on their vision systems very intensively when they are in the unpredictable and dynamic environments. This work proposes a simple and real-time object recognition system for the RoboCup soccer humanoid league rules of the 2009 competition. This vision system can help the robot to collect various environment information as the terminal data to complete the functions of robot localization, robot tactic, barrier avoiding, etc. It can reduce the computing complexity by using our proposed approach, adaptive resolution method (ARM), to recognize the critical objects in the contest field by object features which can be obtained easily. The experimental results indicate that the proposed approach can increase the real-time and accurate recognition efficiency.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙

Adaptive vision-based self-localization system for humanoid robot of RoboCup

[[abstract]]Robotic soccer games represent the most significant form of research in artificial intelligence. Using the humanoid soccer robot’s basic movement and strategic actions, the robot takes part in a dynamic and unpredictable contest and must recognize its own position on the field at all times. Therefore, the localization system for the soccer robot represents the key technology for improving its performance. This work proposes a new approach for self-localization, an Adaptive Vision-Based Self-Localization System (AVBSLS), which allows the humanoid robot to integrate the information from the pan/tilt motors and a single camera to achieve self-localization. The proposed approach uses a measuring artificial neural network technique to adjust the position of the humanoid robot. A systematic method to measure the intrinsic parameters is proposed for the CCD camera adjustment. Using this approach, any type of CCD camera can be used to precisely calculate the robot’s position. The experimental results indicate that the average accuracy of the localization is 92.3% for a frame rate of 15 frames per second (FPS).[[incitationindex]]SCI[[booktype]]電子

Memory-efficient hardware architecture of 2-D dual-mode lifting-based discrete wavelet transform

[[abstract]]Memory requirements (for storing intermediate signals) and critical path are the essential issues for two-dimensional (2-D) (or multi-dimensional) transforms. This work presents new algorithms and hardware architectures to address the above issues in 2-D dual-mode (supporting 5/3 lossless and 9/7 lossy coding) Lifting-based Discrete Wavelet Transform (LDWT). The proposed 2-D dual-mode LDWT architecture has the merits of low-transpose memory, low latency, and regular signal flow, making it suited for VLSI implementation. The transpose memory requirement of the N×N 2-D 5/3 mode LDWT and 2-D 9/7 mode LDWT are 2N and 4N, respectively. Comparison results indicate that the proposed hardware architecture has a lower lifting-based low-transpose memory size requirement than the previous architectures. As a result, it can be applied to real-time visual operations such as JPEG2000, Motion-JPEG2000, MPEG-4 still texture object decoding, and wavelet-based scalable video coding (SVC) applications.[[incitationindex]]SCI[[booktype]]紙

A fast discrete wavelet transform algorithm for visual processing applications

[[abstract]]For visual processing applications, the two-dimensional (2-D) Discrete Wavelet Transform (DWT) can be used to decompose an image into four-subband images. However, when a single band is required for a specific application, the four-band decomposition demands a huge complexity and transpose time. This work presents a fast algorithm, namely 2-D Symmetric Mask-based Discrete Wavelet Transform (SMDWT), to address some critical issues of the 2-D DWT. Unlike the traditional DWT involving dependent decompositions, the SMDWT itself is subband processing independent, which can significantly reduce complexity. Moreover, DWT cannot directly obtain target subbands as mentioned, which leads to an extra wasting in transpose memory, critical path, and operation time. These problems can be fully improved with the proposed SMDWT. Nowadays, many applications employ DWT as the core transformation approach, the problems indicated above have motivated researchers to develop lower complexity schemes for DWT. The proposed SMDWT has been proved as a highly efficient and independent processing to yield target subbands, which can be applied to real-time visual applications, such as moving object detection and tracking, texture segmentation, image/video compression, and any possible DWT-based applications.[[incitationindex]]SCI[[booktype]]紙

A Stereo Vision-Based Self-Localization System

[[abstract]]This paper proposes a new stereo vision-based self-localization system (SVBSLS) for the RoboCup soccer humanoid league rules for the 2010 competition. The humanoid robot integrates information from pan/tilt motors and stereo vision to accomplish the self-localization and measure the distance from the robot to the soccer ball. The proposed approach uses a trigonometric function to find coarse distances from the robot to the landmark and from the robot to the soccer ball, after which it adopts an artificial neural network technique to increase the precision of the distance measurement. A statistics approach is also used to calculate the relationship between the humanoid robot and the position of the landmark for self-localization. The experimental results indicate that the SVBSLS localization system in this paper had an accuracy ratio of 100 for localization. The average error of distance from the humanoid soccer robot to the soccer ball was only 0.64 cm.[[incitationindex]]SCI[[booktype]]紙