Fabric defects detection using adaptive wavelets

Purpose – Fabric defects detection is vital in the automation of textile industry. The purpose of this paper is to develop and implement a new fabric defects detection method based on adaptive wavelet. Design/methodology/approach – Fabric defects can be regarded as the abrupt features of textile images with uniform background textures. Wavelets have compact support and can represent these textures. When there is an abrupt feature existed, the response is totally different with the response of the background textures, so wavelets can detect these abrupt features. This method designs the appropriate wavelet bases for different fabric images adaptively. The defects can be detected accurately. Findings – The proposed method achieves accurate detection of fabric defects. The experimental results suggest that the approach is effective. Originality/value – This paper develops an appropriate method to design wavelet filter coefficients for detecting fabric defects, which is called adaptive wavelet. And it is helpful to realize the automation of textile industry.

Smartphone Homecare Monitoring of Hearts

Homecare monitoring blood pressures and heartbeats are commercially available using dedicated devices, for example, wrist watch, pulse oximetry. With the advent of Smartphone and compressive sensing technology, we wish to monitor precisely the electrical waveforms of heartbeats called the electrocardiography (ECG) for an aging global villager biomedical wellness homecare system. Our design separates into 3 innovative modules within the size-weight and power-cost bandwidth (Swap-CB) limitation. We develop each separately but in concert with one another: (i) Smart Electrode (adopting a low-power-mixed signal embedded with modern compressive sensing firmware and applying the nanotechnology to improve the electrodes’ contact impedance as well as novel transduction mechanism, between ECG and electronics, e.g., a pressure mattress coupling, or fiber-optics coupling); (ii) Learnable Database (utilizing adaptive wavelets transforms for systolic and diastolic P-QRS-T-U features extraction Aided Target Recognition and adopting Sequential Query Language for a relational database allowing distant monitoring and retrievable); (iii) Smartphone (inheriting a large touch screen interface display with powerful computation capability and assisting caretaker reporting system with GPS and ID and two-way interaction with patient panic button for programmable emergence reporting procedure). While (i) is novel, (ii) and (iii) are mature. Together, they can eventually provide a supplementary home screening system for the post- or the prediagnosis care at home with a built-in database searchable with the time, the place, and the degree of urgency happened, using in situ screening.