An unsupervised method for detecting smooth contours in digital images is proposed. Following the a contrario approach, the starting point is defining the conditions where contours should not be detected: soft gradient regions contaminated by noise. To achieve this, low frequencies are removed from the input image. Then, contours are validated as the frontiers separating two adjacent regions, o...

In this system we improved the performance of an automatic system for extracting leaf contour. The proposed leaf contour extraction method consists of three major procedures: the detection of four edge points, and contour tracing. Leaf detection includes two stages: feature extraction and matching. For the leaf contour extraction part, we present a new technique for automatically identifying th...

Lip contour detection is regarded as an essential issue in many applications such as personal identification, facial expressions classification, and man-machine interaction. Moreover, semi-supervised learning is utilized to automatically exploit unlabeled data in addition to labeled data to improve the performance of certain machine learning approaches. In this paper, three contour preprocessin...

Moving object target detection has a significant interest in image analysis. Frames are extracted from the real-time video, and from this image the required target is detected. This paper presents a contour-based object tracking using the spatial information. The image is applied for multiple segmentations to partition the image into simpler segments. Then automatic identification is done using...

The arrival of appearance-based image features has dramatically influenced the field of visual object recognition. Previous work has shown, however, that contour curvature and junctions are important for shape representation and detection. We investigate a local representation of contours for object detection that complements appearance-based information, such as texture. We present a non-param...

Contour detection may be mediated by lateral interactions between neighboring cortical neurons whose receptive fields have collinear axes of preferred orientation. This hypothesis was tested in psychophysical experiments and computer simulations using a contour detection task in which observers searched for groups of Gabor patches that followed spatially extended contour paths embedded in noise...

We address the problem of contour detection via per-pixel classifications of edge point. To facilitate the process, the proposed approach leverages with DenseNet, an efficient implementation of multiscale convolutional neural networks (CNNs), to extract an informative feature vector for each pixel and uses an SVM classifier to accomplish contour detection. In the experiment of contour detection...

Extraction and reconstruction of rectal wall structures from an ultrasound image is helpful for surgeons in rectal clinical diagnosis and 3-D reconstruction of rectal structures from ultrasound images. The primary task is to extract the boundary of the muscular layers on the rectal wall. However, due to the low SNR from ultrasound imaging and the thin muscular layer structure of the rectum, thi...

In contour integration, a relevant question is whether snakes and ladders are processed similarly. Higher presentation time thresholds for ladders in detection tasks indicate this is not the case. However, in a detection task only processing differences at the level of element linking and possibly contour localization might be picked up, while differences at the shape encoding level cannot be n...

Contour integration is a fundamental visual process. The constraints on integrating discrete contour elements and the associated neural mechanisms have typically been investigated using static contour paths. However, in our dynamic natural environment objects and scenes vary over space and time. With the aim of investigating the parameters affecting spatiotemporal contour path integration, we m...