From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Steel is the material of choice for a large number and very diverse industrial applications. Surface qualities along with other properties are the most important quality parameters, particularly for flat-rolled steel products. Traditional manual surface inspection procedures are awfully inadequate to ensure guaranteed quality-free surface. To ensure stringent requirements of customers, automated vision-based steel surface inspection techniques have been found to be very effective and popular during the last two decades. Considering its importance, this paper attempts to make the first formal review of state-of-art of vision-based defect detection and classification of steel surfaces as they are produced from steel mills. It is observed that majority of research work has been undertaken for cold steel strip surfaces which is most sensitive to customers' requirements. Work on surface defect detection of hot strips and bars/rods has also shown signs of increase during the last 10 years. The review covers overall aspects of automatic steel surface defect detection and classification systems using vision-based techniques. Attentions have also been drawn to reported success rates along with issues related to real-time operational aspects.

https://link.springer.com/content/pdf/10.1186%2F1687-5281-2014-50.pdf

Review of vision-based steel surface inspection systems

Automated computer-vision-based defect detection has received much attention with the increasing surface quality assurance demands for the industrial manufacturing of flat steels. This article attempts to present a comprehensive survey on surface defect detection technologies by reviewing about 120 publications over the last two decades for three typical flat steel products of con-casting slabs and hot- and cold-rolled steel strips. According to the nature of algorithms as well as image features, the existing methodologies are categorized into four groups: statistical, spectral, model-based, and machine learning. These works are summarized in this review to enable easy referral to suitable methods for diverse application scenarios in steel mills. Realization recommendations and future research trends are also addressed at an abstract level.

/pdf/automated-visual-defect-detection-for-flat-steel-surface-a-3wjhcxn3aa.pdf

Automated Visual Defect Detection for Flat Steel Surface: A Survey

The increasing number of people playing games on touch-screen mobile phones raises the question of whether touch behaviors reflect players’ emotional states. This prospect would not only be a valuable evaluation indicator for game designers, but also for real-time personalization of the game experience. Psychology studies on acted touch behavior show the existence of discriminative affective profiles. In this article, finger-stroke features during gameplay on an iPod were extracted and their discriminative power analyzed. Machine learning algorithms were used to build systems for automatically discriminating between four emotional states (Excited, Relaxed, Frustrated, Bored), two levels of arousal and two levels of valence. Accuracy reached between 69p and 77p for the four emotional states, and higher results (~89p) were obtained for discriminating between two levels of arousal and two levels of valence. We conclude by discussing the factors relevant to the generalization of the results to applications other than games.

/pdf/what-does-touch-tell-us-about-emotions-in-touchscreen-based-4c97ojgqtq.pdf

What Does Touch Tell Us about Emotions in Touchscreen-Based Gameplay?

Machine vision based condition monitoring and fault diagnosis of machine tools using information from machined surface texture: A review

An online surface inspection system of hot rolled strips is introduced. This system is designed to detect such main surface defects on hot rolled strips as scar, scratches, pits, cracks, cross hatchings, and so on. Multiple CCD area scan cameras are adopted to capture images of strip surface simultaneously, and all the images are processed by parallel computation system real-time, which is supported by fast image process techniques and parallel computation techniques, in order to snap main defect regions on the surface of strips. At last, the defects will be classified to several types. The application of the system to a practical production line shows that it can detect main defects of hot rolled strips more effectively than traditional method, and it is easily to be maintained.

Design of online surface inspection system of hot rolled strips

In this paper, we propose an improved Maxshift method in Part 1 of JPEG2000. The proposed algorithm performs compression of an image that includes one or more ROI (region of interest) according to a demand of client using Maxshift method. We evaluate the performance of the proposed method with different bit rates. As a result of simulation, it shows that the proposed method increases PSNR vs. compression ratio performance and makes possible to transmit image with multiple ROIs over low bit rates above the Maxshift method.

The coding technique of image with multiple ROIs using standard Maxshift method

VoIP (Voice over IP), so called Internet phone, provides several unique advantages, for instance, inexpensive long distance call service than the existing wire telephone network and various multimedia services from Internet network added to voice call service. The paper is intended to describe the results of the VoIP system designed and realized by using SIP, which was suggested to create, modify and end multimedia sessions. The VoIP system was developed as an Ads-receiving VoIP terminal, which may receive and save multimedia advertisement and the advertisement service model was suggested. The VoIP phone may save the advertisements received from a PUSH server of common carriers in its internal storage while it saves only the information necessary for a user and delivers it promptly at any time. Regarding the performance of the Ads-receiving VoIP phone, its processing time per kernel instruction, which is the time elapsed to form a packet and transmit it, was 18 ms. As a result of running the software, the receiver only accounted for 4 ms of the software processing time and connecting and disconnecting an outbound call took 93 ms, suggesting the result of 10 ~ 12 calls processed per second.

Improved VoIP Design for the Advertisement Service

Based on researching parameter optimization method of neural network deeply, a new parameter optimization method is presented and applied to surface defect online inspection system of cold rolled strips. The method takes advantages of small-samples fully, and can get a group of neural network parameters which can mostly express the neural network under a certain specific condition. The method is advantageous for its simplicity, easy to maintain and fast, it can be applied to many fields too, such as iron-steel industry, medicine. Experiments showed that a best recognition effect by using the parameters for neural network which are achieved by the new parameter optimization method can be got among all the parameters optimized randomly for surface defect of cold rolled strips.

Research on Parameter Optimization of Neural Network

In this paper, we introduce a rank-based image transformation which is pre-processing method for gray-level images to be compressed more efficiently by entropy encoder. Before entropy encoding a stream of gray-level values in an image, the proposed method counts co-occurrence frequencies for neighboring pixel values. Then, it replaces each pairs of adjacent gray values with particular ordered number based on the investigated co-occurrence frequencies. Finally, the method transmits the adjusted data which has ordered number to entropy encoder. Because statistical characteristic is more enhanced by this preprocessing step, it is possible to improve performance of entropy coding. From the simulation result using 8 bits gray-scale images, it is verified that the proposed method can reduce bit rate by up to 37.85% than plain entropy coders.

Hoon-Sung Kwak

Papers

Design of online surface inspection system of hot rolled strips

The coding technique of image with multiple ROIs using standard Maxshift method

Improved VoIP Design for the Advertisement Service

Research on Parameter Optimization of Neural Network

Rank-based image transformation for entropy coding efficiently