Revisiting SIFT for plant foliage in RGB images acquired on a turntable

In this work, SIFT features are revisited for their use in two applications of computer vision for plant analysis. The first application is the reconstruction of 3D models of plants through tracking homologue points in successive intensity images. The second application is to provide a new global descriptor that gives a measure of the level of self-similariy of foliage for plants of different architectures and foliar appearance. In order to properly exploit SIFT descriptors in relation to these applications, we discuss two aspects of the classical SIFT keypoint matching practice. On the one hand we propose to match detected keypoints based on a scale criterion. On the other hand, we drop the ratio rule while matching keypoints in two images and propose the use of a spatial proximity filter instead

Modèle stochastique et représentation par graphe pour le suivi spatio-temporel de pathogènes à la surface de feuilles par imagerie

Modèle stochastique et représentation par graphe pour le suivi spatio-temporel de pathogènes à la surface de feuilles par imagerie

N-acetylcysteine Facilitates Self-Imposed Abstinence After Escalation of Cocaine Intake.

BACKGROUND: N-acetylcysteine (NAC) has been suggested to prevent relapse to cocaine seeking. However, the psychological processes underlying its potential therapeutic benefit remain largely unknown. METHODS: We investigated the hallmark features of addiction that were influenced by chronic NAC treatment in rats given extended access to cocaine: escalation, motivation, self-imposed abstinence in the face of punishment, or propensity to relapse. For this, Sprague Dawley rats were given access either to 1 hour (short access) or 6 hours (long access [LgA]) self-administration (SA) sessions until LgA rats displayed a robust escalation. Rats then received daily saline or NAC (60 mg/kg, intraperitoneal) treatment and were tested under a progressive ratio and several consecutive sessions in which lever presses were punished by mild electric foot shocks. RESULTS: NAC increased the sensitivity to punishment in LgA rats only, thereby promoting abstinence. Following the cessation of punishment, NAC-treated LgA rats failed to recover fully their prepunishment cocaine intake levels and resumed cocaine SA at a lower rate than short access and vehicle-treated LgA rats. However, NAC altered neither the escalation of SA nor the motivation for cocaine. At the neurobiological level, NAC reversed cocaine-induced decreases in the glutamate type 1 transporter observed in both the nucleus accumbens and the dorsolateral striatum. NAC also increased the expression of Zif268 in the nucleus accumbens and dorsolateral striatum of LgA rats. CONCLUSIONS: Our results indicate that NAC contributes to the restoration of control over cocaine SA following adverse consequences, an effect associated with plasticity mechanisms in both the ventral and dorsolateral striatum.This research was supported by a French Institute of Health and Medical Research Avenir and an ANR12 SAMA00201 Grant (to DB) as well as a Newton Trust/Cambridge University Grant (to DB). BJE and JEM are supported by a Medical Research Council (G9536855, G0701500) Grant to BJE and by a joint award from the Medical Research Council and Wellcome Trust in support of the Behavioral and Clinical Neuroscience Institute at Cambridge University

Low-cost image annotation for supervised machine learning. Application to the detection of weeds in dense culture

An open problem in robotized agriculture is to detect weeds in dense culture. This problem can be addressed with computer vision and machine learning. The bottleneck of supervised approaches lay in the manual annotation of training images. We propose two different approaches for detecting weeds position to speed up this process. The first approach is using synthetic images and eye-tracking to annotated images [4] which is at least 30 times faster than manual annotation by an expert, the second approach is based on real RGB and depth images collected via Kinect v2 sensor. We generated a data set of 150 synthetic images which weeds were randomly positioned on it. Images were gazed by two observers. Eye tracker sampled eye position during the execution of this task [5, 6]. Area of interest was recorded as rectangular patches. A patch is considered as including weeds if the average fixation time in this patch exceeds 1.04 seconds. The quality of visual annotation by eye-tracking is assessed by two ways. First, direct comparison of visual annotation with ground-truth which is shown an average 94.7% of all fixations on an image which fell within ground-truth bounding-boxes. Second, as shown in fig.1 eye-tracked annotated data is used as a training data set in four machine learning approaches and compare the recognition rate with the ground-truth. These four machine learning methods are tested in order to assess the quality of the visual annotation. These methods correspond to handcrafted features adapted to texture characterization. They are followed by a linear support vector machine binary classifier. The table 1 gives the average accuracy and standard deviation. Experimental results prove that visual eye-tracked annotated data are almost the same as in-silico ground-truth and performances of supervised machine learning on eye-tracked annotated data are very close to the one obtained with ground-truth

ElonCam : Système de vision pour mesurer la croissance des plantules en phase hétérotrophe

Système de vision pour mesurer la croissance des plantules en phase hétérotrophe

On the value of the Kullback-Leibler divergence for cost-effective spectral imaging of plants by optimal selection of wavebands

The practical value of a criterion based on statistical information theory is demonstrated for the selection of optimal wavelength and bandwidth of low-cost lighting systems in plant imaging applications. Kullback–Leibler divergence is applied to the problem of spectral band reduction from hyperspectral imaging. The results are illustrated on various plant imaging problems and show similar results to the one obtained with state-of-the-art criteria. A specific interest of the proposed approach is to offer the possibility to integrate technological constraints in the optimization of the spectral bands selected

Différentes modalités d'imagerie (visible, thermographie, hyperspectrale) pour le phénotypage des semences et plantules

Différentes modalités d\u27imagerie (visible, thermographie, hyperspectrale) pour le phénotypage des semences et plantules

Instrumentation and digital image processing for multimodality imagery applied to seeds and seedlings

Instrumentation and digital image processing for multimodality imagery applied to seeds and seedlings