Recently several research works propose image segmentation algorithms using MSER. However they aim at segmenting out specific regions corresponding to user-defined objects. This paper proposes a novel algorithm based on MSER which segments natural images without user intervention and captures multi-scale structure. The algorithm collects MSERs and then partitions whole image plane by redrawing ...

The paper considers the conventional decision feedback equaliser (DFE) that employs a linear combination of the channel observations and past decisions. An expression of the symbol error rate (SER) is derived for the linear-combiner DFE with the general M-PAM constellation by utilising a geometric translation property of decision feedback. A method is developed to optimise the coefficients of t...

This paper describes the signature as a one of the most robust and widely used trait in biometric verification. The signature is also known as behavioral biometric property. We present comparative analysis of offline signature recognition based on Dynamic Time Warping (DTW) and Maximally Stable Extremely Regions (MSER). The MSER system reported accuracy of 95. 371% where FAR is 5. 25% and FRR i...

This work presents a robust online learning and recognition system. The basic idea is to exploit information from tracking an object during the recognition and/or learning stage to obtain increased robustness and better recognition results. Object tracking by means of an extended MSER tracker is utilized to detect local features and construct their trajectories. Compact object representations a...

Extraction of text embedded in scene images has many applications, such as license plate recognition, content based retrieval, text based indexing etc. As the appearances of the text in images are unpredictable, separating text pixels from the background is a challenging one. A new frame work is introduced here which uses edge enhanced MSER along with connected components for text extraction. C...

In a comprehensive study of methods for dealing with the problem of the initial transient, Hoad et al. (2008) determined that the MSER (White, 1997) was an efficient and effective truncation rule appropriate for automation. In this paper, we suggest that the MSER works well because it minimizes an approximation to the mean-squared error in the estimated steady-state mean. Using the example of a...

Detection of local features which are distinctive, invariant and discriminative is used to construct compact image representations in many computer vision applications. Achieving robustness against viewpoint change motivated the development of affine invariant detectors responding to image gradient or contrast changes, edges or corners. We focus on the Maximally Stable Extremal Regions (MSER) d...

The visual analysis of foods on social media by using food recognition algorithm provides valuable insight from the health, cultural and marketing. Food offers a means to automatically recognise as well useful information such calories nutritional estimation image processing machine learning technique. interest points in can be detected effectively Maximally Stable Extremal Region (MSER). As MS...

Ejection phase indices such as mean velocity of circumferential fiber shortening (V-cf), ejection fraction (EF), and mean normalized systolic ejection rate (MSER) are thought to reflect the level of left ventricular (LV) inotropic state. Although known to be influenced by changes in afterload, their response to altered preload is less certain. This question was examined in ten normal subjects s...

The classification of ultrasound scan images is important in monitoring the development prenatal and maternal structures. This paper proposes a big data system for Doppler that combines residual maximally stable extreme regions speeded up robust features (SURF) with decision tree classifier. algorithm first preprocesses before detecting extremal (MSER). A few essential are chosen from MSER regi...